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Graph Learning Reading List

I scanned over the accepted paper lists of top machine learning and data mining conferences for interests in graph learning. We also add a snippset tutorial Parse Website to teach you how to obtain the titles and authors from the official conference website.

We also create the reading lists for 2022 and 2023 for convenience.

Contents

AAAI-2025

  1. RingFormer: A Ring-Enhanced Graph Transformer for Organic Solar Cell Property Prediction

    Zhihao Ding, Ting Zhang, Yiran Li, Jieming Shi, Chen Jason Zhang

  2. FactorGCL: A Hypergraph-Based Factor Model with Temporal Residual Contrastive Learning for Stock Returns Prediction

    Yitong Duan, Weiran Wang, Jian Li

  3. Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedges

    Meixia He, Peican Zhu, Keke Tang, Yangming Guo

  4. HHAN: Comprehensive Infectious Disease Source Tracing via Heterogeneous Hypergraph Neural Network

    Qiang He, Yunting Bao, Hui Fang, Yuting Lin, Hao Sun

  5. VerilogCoder: Autonomous Verilog Coding Agents with Graph-based Planning and Abstract Syntax Tree (AST)-based Waveform Tracing Tool

    Chia-Tung Ho, Haoxing Ren, Brucek Khailany

  6. PRAGA: Prototype-aware Graph Adaptive Aggregation for Spatial Multi-modal Omics Analysis

    Xinlei Huang, Zhiqi Ma, Dian Meng, Yanran Liu, Shiwei Ruan, Qingqiang Sun, Xubin Zheng, Ziyue Qiao

  7. Social Recommendation via Graph-Level Counterfactual Augmentation

    Yinxuan Huang, Ke Liang, Yanyi Huang, Xiang Zeng, Kai Chen, Bin Zhou

  8. Graph-Based Cross-Domain Knowledge Distillation for Cross-Dataset Text-to-Image Person Retrieval

    Bingjun Luo, Jinpeng Wang, Zewen Wang, Junjie Zhu, Xibin Zhao

  9. GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction

    Yuwei Miao, Yuzhi Guo, Hehuan Ma, Jingquan Yan, Feng Jiang, Rui Liao, Junzhou Huang

  10. Robust Heterogeneous Graph Classification for Molecular Property Prediction with Information Bottleneck

    Zhibin Ni, Chang Liu, Hai Wan, Xibin Zhao

  11. Dual-Channel Interactive Graph Transformer for Traffic Classification with Message-Aware Flow Representation

    Xing Qiu, Guang Cheng, Weizhou Zhu, Dandan Niu, Nan Fu

  12. NEST: A Neuromodulated Small-world Hypergraph Trajectory Prediction Model for Autonomous Driving

    Chengyue Wang, Haicheng Liao, Bonan Wang, Yanchen Guan, Bin Rao, Ziyuan Pu, Zhiyong Cui, Cheng-Zhong Xu, Zhenning Li

  13. Hybrid-Driving: An Autonomous Driving Decision Framework Integrating Large Language Models, Knowledge Graphs and Driving Rules

    Jiabao Wang, Zepeng Wu, Qian Dong, Lingzhong Meng, Yunzhi Xue, Yukuan Yang

  14. Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization

    Lirong Wu, Haitao Lin, Yufei Huang, Zhangyang Gao, Cheng Tan, Yunfan Liu, Tailin Wu, Stan Z. Li

  15. Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales

    Xinyu Yang, Yu Sun, Xinyang Chen, Ying Zhang, Xiaojie Yuan

  16. Disentangled Table-Graph Representation for Interpretable Transmission Line Fault Location

    Na Yu, Yutong Deng, Shunyu Liu, Kaixuan Chen, Tongya Zheng, Mingli Song

  17. Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model

    Haozhen Zhang, Haodong Yue, Xi Xiao, Le Yu, Qing Li, Zhen Ling, Ye Zhang

  18. Dynamic Interactive Bimodal Hypergraph Networks for Emotion Recognition in Conversations

    Xuping Chen, Wuzhen Shi

  19. Knowledge-Enhanced Hierarchical Heterogeneous Graph for Personality Identification with Limited Training Data

    Yuxuan Song, Qiudan Li, Yilin Wu, David Jingjun Xu, Daniel Dajun Zeng

  20. DepMGNN: Matrixial Graph Neural Network for Video-based Automatic Depression Assessment

    Zijian Wu, Leijing Zhou, Shuanglin Li, Changzeng Fu, Jun Lu, Jing Han, Yi Zhang, Zhuang Zhao, Siyang Song

  21. Deep Graph Online Hashing for Multi-Label Image Retrieval

    Yuan Cao, Xiangru Chen, Zifan Liu, Wenzhe Jia, Fanlei Meng, Jie Gui

  22. 3DPGS: 3D Probabilistic Graph Search for Archaeological Piece Grouping

    Junfeng Cheng, Yingkai Yang, Tania Stathaki

  23. Graphic Design with Large Multimodal Model

    Yutao Cheng, Zhao Zhang, Maoke Yang, Hui Nie, Chunyuan Li, Xinglong Wu, Jie Shao

  24. Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion

    Yuqin Dai, Wanlu Zhu, Ronghui Li, Zeping Ren, Xiangzheng Zhou, Jixuan Ying, Jun Li, Jian Yang

  25. LLaVA Needs More Knowledge: Retrieval Augmented Natural Language Generation with Knowledge Graph for Explaining Thoracic Pathologies

    Ameer Hamza, Abdullah , Yong Hyun Ahn, Sungyoung Lee, Seong Tae Kim

  26. DAMPER: A Dual-Stage Medical Report Generation Framework with Coarse-Grained MeSH Alignment and Fine-Grained Hypergraph Matching

    Xiaofei Huang, Wenting Chen, Jie Liu, Qisheng Lu, Xiaoling Luo, Linlin Shen

  27. What Kind of Visual Tokens Do We Need? Training-Free Visual Token Pruning for Multi-Modal Large Language Models from the Perspective of Graph

    Yutao Jiang, Qiong Wu, Wenhao Lin, Wei Yu, Yiyi Zhou

  28. Relation-aware Hierarchical Prompt for Open-vocabulary Scene Graph Generation

    Tao Liu, Rongjie Li, Chongyu Wang, Xuming He

  29. Infer the Whole from a Glimpse of a Part: Keypoint-Based Knowledge Graph for Vehicle Re-Identification

    Kai Lv, Yunlong Li, Zhuo Chen, Shuo Wang, Sheng Han, Youfang Lin

  30. A Trusted Lesion-assessment Network for Interpretable Diagnosis of Coronary Artery Disease in Coronary CT Angiography

    Xinghua Ma, Xinyan Fang, Mingye Zou, Gongning Luo, Wei Wang, Kuanquan Wang, Zhaowen Qiu, Xin Gao, Shuo Li

  31. HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation

    Ba Hung Ngo, Doanh C. Bui, Nhat-Tuong Do-Tran, Tae Jong Choi

  32. Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation

    Thong Thanh Nguyen, Xiaobao Wu, Yi Bin, Cong-Duy T Nguyen, See-Kiong Ng, Anh Tuan Luu

  33. Beyond Text: Fine-Grained Multi-Modal Fact Verification with Hypergraph Transformers

    Hui Pang, Chaozhuo Li, Litian Zhang, Senzhang Wang, Xi Zhang

  34. SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation

    Shi-Feng Peng, Guolei Sun, Yong Li, Hongsong Wang, Guo-Sen Xie

  35. TGBFormer: Transformer-GraphFormer Blender Network for Video Object Detection

    Qiang Qi, Xiao Wang

  36. Motif Guided Graph Transformers with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification

    Haocong Rao, Chunyan Miao

  37. Dual-branch Graph Feature Learning for NLOS Imaging

    Xiongfei Su, Tianyi Zhu, Lina Liu, Zheng Chen, Yulun Zhang, Siyuan Li, Juntian Ye, Feihu Xu, Xin Yuan

  38. Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection

    Fenfang Tao, Guo-Sen Xie, Fang Zhao, Xiangbo Shu

  39. Scene Graph-Grounded Image Generation

    Fuyun Wang, Tong Zhang, Yuanzhi Wang, Xiaoya Zhang, Xin Liu, Zhen Cui

  40. BLS-GAN: A Deep Layer Separation Framework for Eliminating Bone Overlap in Conventional Radiographs

    Haolin Wang, Yafei Ou, Prasoon Ambalathankandy, Gen Ota, Pengyu Dai, Masayuki Ikebe, Kenji Suzuki, Tamotsu Kamishima

  41. Deep Multi-modal Graph Clustering via Graph Transformer Network

    Qianqian Wang, Haiming Xu, Zihao Zhang, Wei Feng, Quanxue Gao

  42. Imagine: Image-Guided 3D Part Assembly with Structure Knowledge Graph

    Weihao Wang, Yu Lan, Mingyu You, Bin He

  43. HomoMatcher: Achieving Dense Feature Matching with Semi-Dense Efficiency by Homography Estimation

    Xiaolong Wang, Lei Yu, Yingying Zhang, Jiangwei Lao, Lixiang Ru, Liheng Zhong, Jingdong Chen, Yu Zhang, Ming Yang

  44. GraphAvatar: Compact Head Avatars with GNN-Generated 3D Gaussians

    Xiaobao Wei, Peng Chen, Ming Lu, Hui Chen, Feng Tian

  45. Achieving Lightweight Super-Resolution for Real-Time Computer Graphics

    Yu Wen, Chen Zhang, Chenhao Xie, Xin Fu

  46. Semi-Supervised Clustering Framework for Fine-grained Scene Graph Generation

    Jiarui Yang, Chuan Wang, Jun Zhang, Shuyi Wu, Jinjing Zhao, Zeming Liu, Liang Yang

  47. MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation

    Zhifei Yang, Keyang Lu, Chao Zhang, Jiaxing Qi, Hanqi Jiang, Ruifei Ma, Shenglin Yin, Yifan Xu, Mingzhe Xing, Zhen Xiao, Jieyi Long, Xiangde Liu, Guangyao Zhai

  48. GRPose: Learning Graph Relations for Human Image Generation with Pose Priors

    Xiangchen Yin, Donglin Di, Lei Fan, Hao Li, Wei Chen, Gouxiaofei , Yang Song, Xiao Sun, Xun Yang

  49. RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning

    Kanghoon Yoon, Kibum Kim, Jaehyeong Jeon, Yeonjun In, Donghyun Kim, Chanyoung Park

  50. Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics

    Kaiwei Zhang, Dandan Zhu, Xiongkuo Min, Guangtao Zhai

  51. SIGraph: Saliency Image-Graph Network for Retinal Disease Classification in Fundus Image

    Peng Zhang, Yuan Li, Haotian Song, Yankai Jiang, Yubo Tao, Hai Lin, Hongguang Cui

  52. SGDiff: Scene Graph Guided Diffusion Model for Image Collaborative SegCaptioning

    Xu Zhang, Jin Yuan, Hanwang Zhang, Guojin Zhong, Yongsheng Zang, Jiacheng Lin, Zhiyong Li

  53. Dynamic Entity-Masked Graph Diffusion Model for Histopathology Image Representation Learning

    Zhenfeng Zhuang, Min Cen, Yanfeng Li, Fangyu Zhou, Lequan Yu, Baptiste Magnier, Liansheng Wang

  54. Breaking Symmetries in Quantified Graph Search: A Comparative Study

    Mikoláš Janota, Markus Kirchweger, Tomáš Peitl, Stefan Szeider

  55. Motif-aware Graph Neural Networks for Networked Time Series Imputation

    Nourhan Ahmed, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme

  56. Revisiting Multimodal Emotion Recognition in Conversation from the Perspective of Graph Spectrum

    Wei Ai, Fuchen Zhang, Yuntao Shou, Tao Meng, Haowen Chen, Keqin Li

  57. Alleviating Performance Disparity in Adversarial Spatiotemporal Graph Learning Under Zero-Inflated Distribution

    Songran Bai, Yuheng Ji, Yue Liu, Xingwei Zhang, Xiaolong Zheng, Daniel Dajun Zeng

  58. LLM-DR: A Novel LLM-Aided Diffusion Model for Rule Generation on Temporal Knowledge Graphs

    Kai Chen, Xin Song, Ye Wang, Liqun Gao, Aiping Li, Xiaojuan Zhao, Bin Zhou, Yalong Xie

  59. Designing Specialized Two-Dimensional Graph Spectral Filters for Spatial-Temporal Graph Modeling

    Yuxin Chen, Fangru Lin, Jingyi Huo, Hui Yan

  60. Towards Global-Topology Relation Graph for Inductive Knowledge Graph Completion

    Ling Ding, Lei Huang, Zhizhi Yu, Di Jin, Dongxiao He

  61. Global Attribute-Association Pattern Aggregation for Graph Fraud Detection

    Mingjiang Duan, Da He, Tongya Zheng, Lingxiang Jia, Mingli Song, Xinyu Wang, Zunlei Feng

  62. Spatial-Temporal Heterogenous Graph Contrastive Learning for Microservice Workload Prediction

    Mohan Gao, Kexin Xu, Xiaofeng Gao, Tengwei Cai, Haoyuan Ge

  63. Responsive Dynamic Graph Disentanglement for Metro Flow Forecasting

    Qiang Gao, Zizheng Wang, Li Huang, Goce Trajcevski, Guisong Liu, Xueqin Chen

  64. Mixed-Curvature Multi-Modal Knowledge Graph Completion

    Yuxiao Gao, Fuwei Zhang, Zhao Zhang, Xiaoshuang Min, Fuzhen Zhuang

  65. Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation

    Chendi Ge, Xin Wang, Ziwei Zhang, Yijian Qin, Hong Chen, Haiyang Wu, Yang Zhang, Yuekui Yang, Wenwu Zhu

  66. GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

    Zihao Guo, Qingyun Sun, Haonan Yuan, Xingcheng Fu, Min Zhou, Yisen Gao, Jianxin Li

  67. Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation

    Jun Hu, Bryan Hooi, Bingsheng He, Yinwei Wei

  68. Beyond Graph Convolution: Multimodal Recommendation with Topology-aware MLPs

    Junjie Huang, Jiarui Qin, Yong Yu, Weinan Zhang

  69. Multiplex Graph Representation Learning with Homophily and Consistency

    Yudi Huang, Ci Nie, Hongqing He, Yujie Mo, Yonghua Zhu, Guoqiu Wen, Xiaofeng Zhu

  70. HePa: Heterogeneous Graph Prompting for All-Level Classification Tasks

    Jia Jinghong, Lei Song, Jiaxing Li, Youyong Kong

  71. Cluster-guided Contrastive Class-imbalanced Graph Classification

    Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Jianhao Shen, Ziyue Qiao, Ming Zhang

  72. HI-DR: Exploiting Health Status-Aware Attention and an EHR Graph+ for Effective Medication Recommendation

    Taeri Kim, Jiho Heo, Hyunjoon Kim, Sang-Wook Kim

  73. From Your Block to Our Block: How to Find Shared Structure Between Stochastic Block Models over Multiple Graphs

    Iiro Kumpulainen, Sebastian Dalleiger, Jilles Vreeken, Nikolaj Tatti

  74. Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks

    Yeon-Chang Lee, Hojung Shin, Sang-Wook Kim

  75. Feature-Structure Adaptive Completion Graph Neural Network for Cold-start Recommendation

    Songyuan Lei, Xinglong Chang, Zhizhi Yu, Dongxiao He, Cuiying Huo, Jianrong Wang, Di Jin

  76. DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation

    Hourun Li, Yifan Wang, Zhiping Xiao, Jia Yang, Changling Zhou, Ming Zhang, Wei Ju

  77. Self-Explainable Graph Transformer for Link Sign Prediction

    Lu Li, Jiale Liu, Xingyu Ji, Maojun Wang, Zeyu Zhang

  78. Context-aware Inductive Knowledge Graph Completion with Latent Type Constraints and Subgraph Reasoning

    Muzhi Li, Cehao Yang, Chengjin Xu, Zixing Song, Xuhui Jiang, Jian Guo, Ho-fung Leung, Irwin King

  79. Context-aware Graph Neural Network for Graph-based Fraud Detection with Extremely Limited Labels

    Pengbo Li, Hang Yu, Xiangfeng Luo

  80. Structure Balance and Gradient Matching-Based Signed Graph Condensation

    Rong Li, Long Xu, Songbai Liu, Junkai Ji, Lingjie Li, Qiuzhen Lin, Lijia Ma

  81. Unified Graph Neural Networks Pre-training for Multi-domain Graphs

    Mingkai Lin, Xiaobin Hong, Wenzhong Li, Sanglu Lu

  82. THGNets: Constrained Temporal Hypergraphs and Graph Neural Networks in Hyperbolic Space for Information Diffusion Prediction

    Yanchao Liu, Pengzhou Zhang, Wenchao Song, Yao Zheng, Deyu Li, Lei Shi, Junpeng Gong

  83. EPERM: An Evidence Path Enhanced Reasoning Model for Knowledge Graph Question and Answering

    Xiao Long, Liansheng Zhuang, Aodi Li, MingHong Yao, Shafei Wang

  84. Densest k-Subgraph Mining via a Provably Tight Relaxation

    Qiheng Lu, Nicholas D Sidiropoulos, Aritra Konar

  85. FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning

    Renqiang Luo, Huafei Huang, Ivan Lee, Chengpei Xu, Jianzhong Qi, Feng Xia

  86. Dynamic Multi-Interest Graph Neural Network for Session-Based Recommendation

    Mingyang Lv, Xiangfeng Liu, Yuanbo Xu

  87. S²DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion

    Tengfei Ma, Yujie Chen, Liang Wang, Xuan Lin, Bosheng Song, Xiangxiang Zeng

  88. DOGE: LLMs-Enhanced Hyper-Knowledge Graph Recommender for Multimodal Recommendation

    Fanshen Meng, Zhenhua Meng, Ru Jin, Rongheng Lin, Budan Wu

  89. Trust-GRS: A Trustworthy Training Framework for Graph Neural Network Based Recommender Systems Against Shilling Attacks

    Lingyu Mu, Zhengxiao Liu, Zhitong Zhu, Zheng Lin

  90. Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective

    Bo Ni, Yu Wang, Lu Cheng, Erik Blasch, Tyler Derr

  91. LS-TGNN: Long and Short-Term Temporal Graph Neural Network for Session-Based Recommendation

    Zhonghong Ou, Xiao Zhang, Yifan Zhu, Shuai Lyu, Jiahao Liu, Tu Ao

  92. A Label-free Heterophily-guided Approach for Unsupervised Graph Fraud Detection

    Junjun Pan, Yixin Liu, Xin Zheng, Yizhen Zheng, Alan Wee-Chung Liew, Fuyi Li, Shirui Pan

  93. Seeing Beyond Noise: Joint Graph Structure Evaluation and Denoising for Multimodal Recommendation

    Yuxin Qi, Quan Zhang, Xi Lin, Xiu Su, Jiani Zhu, Jingyu Wang, Jianhua Li

  94. GeoMamba: Towards Multi-granular POI Recommendation with Geographical State Space Model

    Yifang Qin, Jiaxuan Xie, Zhiping Xiao, Ming Zhang

  95. Adversarial Contrastive Graph Masked AutoEncoder Against Graph Structure and Feature Dual Attacks

    Weixuan Shen, Xiaobo Shen, Shirui Pan

  96. UniFORM: Towards Unified Framework for Anomaly Detection on Graphs

    Chuancheng Song, Xixun Lin, Hanyang Shen, Yanmin Shang, Yanan Cao

  97. Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics

    Li Sun, Ziheng Zhang, Zixi Wang, Yujie Wang, Qiqi Wan, Hao Li, Hao Peng, Philip S. Yu

  98. GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation

    Shengyin Sun, Wenhao Yu, Yuxiang Ren, Weitao Du, Liwei Liu, Xuecang Zhang, Ying Hu, Chen Ma

  99. Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs

    Xiaqiang Tang, Jian Li, Nan Du, Sihong Xie

  100. Rule-Guided Graph Neural Networks for Explainable Knowledge Graph Reasoning

    Zhe Wang, Suxue Ma, Kewen Wang, Zhiqiang Zhuang

  101. Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration

    Zijian Wang, Bin Wang, Haifeng Jing, Huayu Li, Hongbo Dou

  102. Prompt-based Unifying Inference Attack on Graph Neural Networks

    Yuecen Wei, Xingcheng Fu, Lingyun Liu, Qingyun Sun, Hao Peng, Chunming Hu

  103. Cross-Domain Trajectory Association Based on Hierarchical Spatiotemporal Enhanced Attention Hypergraph

    Chenlong Wu, Ze Wang, Keqing Cen, Yude Bai, Jin Hao

  104. Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training

    Shuyin Xia, Xinjun Ma, Zhiyuan Liu, Cheng Liu, Sen Zhao, Guoyin Wang

  105. Improving Complex Reasoning over Knowledge Graph with Logic-Aware Curriculum Tuning

    Tianle Xia, Liang Ding, Guojia Wan, Yibing Zhan, Bo Du, Dacheng Tao

  106. Robust Graph Based Social Recommendation Through Contrastive Multi-View Learning

    Fei Xiong, Tao Zhang, Shirui Pan, Guixun Luo, Liang Wang

  107. KGCRR: An Effective Metric-Driven Knowledge Graph Completion Framework by Designing a Novel Upper Bound Function with Adaptive Approximation to Reciprocal Rank

    Kuan Xu, Kuo Yang, Jian Liu, Xiangkui Lu, Jun Wu, Xuezhong Zhou

  108. Semantic Enhanced Heterogeneous Hypergraph Network for Collaborative Filtering

    Mingtao Xu, Wei Wei, Peixuan Yang, Hulong Wu

  109. NLGT: Neighborhood-based and Label-enhanced Graph Transformer Framework for Node Classification

    Xiaolong Xu, Yibo Zhou, Haolong Xiang, Xiaoyong Li, Xuyun Zhang, Lianyong Qi, Wanchun Dou

  110. Out-of-Distribution Generalization on Graphs via Progressive Inference

    Yiming Xu, Bin Shi, Zhen Peng, Huixiang Liu, Bo Dong, Chen Chen

  111. Revisiting Graph Contrastive Learning on Anomaly Detection: A Structural Imbalance Perspective

    Yiming Xu, Zhen Peng, Bin Shi, Xu Hua, Bo Dong, Song Wang, Chen Chen

  112. Federated Graph Condensation with Information Bottleneck Principles

    Bo Yan, Sihao He, Cheng Yang, Shang Liu, Yang Cao, Chuan Shi

  113. Harnessing Language Model for Cross-Heterogeneity Graph Knowledge Transfer

    Jinyu Yang, Ruijia Wang, Cheng Yang, Bo Yan, Qimin Zhou, Yang Juan, Chuan Shi

  114. Erase Then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning

    Zhe-Rui Yang, Jindong Han, Chang-Dong Wang, Hao Liu

  115. Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs

    Jianxiang Yu, Yuxiang Ren, Chenghua Gong, Jiaqi Tan, Xiang Li, Xuecang Zhang

  116. Mind Individual Information! Principal Graph Learning for Multimedia Recommendation

    Penghang Yu, Zhiyi Tan, Guanming Lu, Bing-Kun Bao

  117. Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection

    Zhizhi Yu, Chundong Liang, Xinglong Chang, Dongxiao He, Di Jin, Jianguo Wei

  118. Dynamic Graph Learning with Static Relations for Credit Risk Assessment

    Qi Yuan, Yang Liu, Yateng Tang, Xinhuan Chen, Xuehao Zheng, Qing He, Xiang Ao

  119. Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural Networks

    Yanwei Yue, Guibin Zhang, Haoran Yang, Dawei Cheng

  120. Rethinking Cancer Gene Identification Through Graph Anomaly Analysis

    Yilong Zang, Lingfei Ren, Yue Li, Zhikang Wang, David Antony Selby, Zheng Wang, Sebastian Josef Vollmer, Hongzhi Yin, Jiangning Song, Junhang Wu

  121. Core Knowledge Learning Framework for Graph

    Bowen Zhang, Zhichao Huang, Guangning Xu, Xiaomao Fan, Mingyan Xiao, Genan Dai, Hu Huang

  122. DREAM: Decoupled Discriminative Learning with Bigraph-aware Alignment for Semi-supervised 2D-3D Cross-modal Retrieval

    Fan Zhang, Changhu Wang, Zebang Cheng, Xiaojiang Peng, Dongjie Wang, Yijia Xiao, Chong Chen, Xian-Sheng Hua, Xiao Luo

  123. Expand Horizon: Graph Out-of-Distribution Generalization via Multi-Level Environment Inference

    Jiaqiang Zhang, Songcan Chen

  124. Lightweight Yet Fine-Grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-Account Sequential Recommendation

    Jinyu Zhang, Zhongying Zhao, Chao Li, Yanwei Yu

  125. Teacher-guided Edge Discriminator for Personalized Graph Masked Autoencoder

    Qiqi Zhang, Chao Li, Zhongying Zhao

  126. Integrating Large Language Models and Möbius Group Transformations for Temporal Knowledge Graph Embedding on the Riemann Sphere

    Sensen Zhang, Xun Liang, Simin Niu, Zhendong Niu, Bo Wu, Gengxin Hua, Long Wang, Zhenyu Guan, Hanyu Wang, Xuan Zhang, Zhiyu Li, Yuefeng Ma

  127. Highly Imperceptible Black-Box Graph Injection Attacks with Reinforcement Learning

    Maochang Zhao, Jing Zhang

  128. GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs

    Songwei Zhao, Yuan Jiang, Zijing Zhang, Yang Yu, Hechang Chen

  129. TRACI: A Data-centric Approach for Multi-Domain Generalization on Graphs

    Yusheng Zhao, Changhu Wang, Xiao Luo, Junyu Luo, Wei Ju, Zhiping Xiao, Ming Zhang

  130. Dynamic Spectral Graph Anomaly Detection

    Jianbo Zheng, Chao Yang, Tairui Zhang, Longbing Cao, Bin Jiang, Xuhui Fan, Xiao-ming Wu, Xianxun Zhu

  131. Tokenphormer: Structure-aware Multi-token Graph Transformer for Node Classification

    Zijie Zhou, Zhaoqi Lu, Xuekai Wei, Rongqin Chen, Shenghui Zhang, Pak Lon Ip, Leong Hou U

  132. Representation Learning Based Predicate Invention on Knowledge Graphs

    Man Zhu, Pengfei Huang, Lei Gu, Xiaolong Xu, Jingyu Han

  133. Refine then Classify: Robust Graph Neural Networks with Reliable Neighborhood Contrastive Refinement

    Shuman Zhuang, Zhihao Wu, Zhaoliang Chen, Hong-Ning Dai, Ximeng Liu

  134. LOHA: Direct Graph Spectral Contrastive Learning Between Low-Pass and High-Pass Views

    Ziyun Zou, Yinghui Jiang, Lian Shen, Juan Liu, Xiangrong Liu

  135. Last-iterate Convergence in Regularized Graphon Mean Field Game

    Jing Dong, Baoxiang Wang, Yaoliang Yu

  136. Individually Stable Dynamics in Coalition Formation over Graphs

    Angelo Fanelli, Laurent Gourvès, Ayumi Igarashi, Luca Moscardelli

  137. GNN-Transformer Task Planning Enhanced with Semantic-Driven Data Augmentation

    Soojin Jeong, Seongwan Byeon, Sangwoo Kim, HyeokJun Kwon, Yoonseon Oh

  138. Heterogeneous Multi-Robot Graph Coverage with Proximity and Movement Constraints

    Dolev Mutzari, Yonatan Aumann, Sarit Kraus

  139. Online Guidance Graph Optimization for Lifelong Multi-Agent Path Finding

    Hongzhi Zang, Yulun Zhang, He Jiang, Zhe Chen, Daniel Harabor, Peter J. Stuckey, Jiaoyang Li

  140. DPCL-Diff：Temporal Knowledge Graph Reasoning Based on Graph Node Diffusion Model with Dual-Domain Periodic Contrastive Learning

    Yukun Cao, LIsheng Wang, Luobin Huang

  141. Replacing Paths with Connection-Biased Attention for Knowledge Graph Completion

    Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal

  142. APKGC: Noise-enhanced Multi-Modal Knowledge Graph Completion with Attention Penalty

    Yue Jian, Xiangyu Luo, Zhifei Li, Miao Zhang, Yan Zhang, Kui Xiao, Xiaoju Hou

  143. SPAC: Sparse Partitioning and Adaptive Core Tensor Pruning Model for Knowledge Graph Completion

    Chuhong Yang, Bin Li, Nan Wu

  144. Knowledge Graph Completion with Relation-Aware Anchor Enhancement

    Duanyang Yuan, Sihang Zhou, Xiaoshu Chen, Dong Wang, Ke Liang, Xinwang Liu, Jian Huang

  145. Gaussian Graphical Modelling Without Independence Assumptions for Uncentered Data

    Bailey Andrew, David R. Westhead, Luisa Cutillo

  146. When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning

    Naheed Anjum Arafat, Debabrota Basu, Yulia Gel, Yuzhou Chen

  147. Weighted Embeddings for Low-Dimensional Graph Representation

    Thomas Bläsius, Jean-Pierre von der Heydt, Maximilian Katzmann, Nikolai Maas

  148. ML-GOOD: Towards Multi-Label Graph Out-Of-Distribution Detection

    Tingyi Cai, Yunliang Jiang, Ming Li, Changqin Huang, Yi Wang, Qionghao Huang

  149. Global Graph Propagation with Hierarchical Information Transfer for Incomplete Contrastive Multi-view Clustering

    Guoqing Chao, Kaixin Xu, Xijiong Xie, Yongyong Chen

  150. Cross-View Graph Consistency Learning for Invariant Graph Representations

    Jie Chen, Hua Mao, Wai Lok Woo, Chuanbin Liu, Xi Peng

  151. Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation

    Wei Chen, Guo Ye, Yakun Wang, Zhao Zhang, Libang Zhang, Daixin Wang, Zhiqiang Zhang, Fuzhen Zhuang

  152. Beyond Homophily: Graph Contrastive Learning with Macro-Micro Message Passing

    Yiyuan Chen, Donghai Guan, Weiwei Yuan, Tianzi Zang

  153. WatE: A Wasserstein t-distributed Embedding Method for Information-enriched Graph Visualization

    Minjie Cheng, Dixin Luo, Hongteng Xu

  154. Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors

    Jinhyeok Choi, Heehyeon Kim, Joyce Jiyoung Whang

  155. THESAURUS: Contrastive Graph Clustering by Swapping Fused Gromov-Wasserstein Couplings

    Bowen Deng, Tong Wang, Lele Fu, Sheng Huang, Chuan Chen, Tao Zhang

  156. Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation

    Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun, Jianxi Gao

  157. Contrastive Auxiliary Learning with Structure Transformation for Heterogeneous Graphs

    Wei Du, Hongmin Sun, Hang Gao, Gaoyang Li, Ying Li

  158. Learning Regularization for Graph Inverse Problems

    Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber

  159. Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning

    Wenzhe Fan, Zishun Yu, Chengdong Ma, Changye Li, Yaodong Yang, Xinhua Zhang

  160. Large Language Models Enhanced Personalized Graph Neural Architecture Search in Federated Learning

    Hui Fang, Yang Gao, Peng Zhang, Jiangchao Yao, Hongyang Chen, Haishuai Wang

  161. Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning

    Xingbo Fu, Zihan Chen, Yinhan He, Song Wang, Binchi Zhang, Chen Chen, Jundong Li

  162. Discrete Curvature Graph Information Bottleneck

    Xingcheng Fu, Jian Wang, Yisen Gao, Qingyun Sun, Haonan Yuan, Jianxin Li, Xianxian Li

  163. Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck

    Xingcheng Fu, Yisen Gao, Beining Yang, Yuxuan Wu, Haodong Qian, Qingyun Sun, Xianxian Li

  164. HYGENE: A Diffusion-Based Hypergraph Generation Method

    Dorian Gailhard, Enzo Tartaglione, Lirida Naviner, Jhony H. Giraldo

  165. Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach

    Hang Gao, Chenhao Zhang, Fengge Wu, Changwen Zheng, Junsuo Zhao, Huaping Liu

  166. DivGCL: A Graph Contrastive Learning Model for Diverse Recommendation

    Wenwen Gong, Yangliao Geng, Dan Zhang, Yifan Zhu, Xiaolong Xu, Haolong Xiang, Amin Beheshti, Xuyun Zhang, Lianyong Qi

  167. Efficient Graph Bandit Learning with Side-Observations and Switching Constraints

    Xueping Gong, Jiheng Zhang

  168. Neural Temporal Point Processes for Forecasting Directional Relations in Evolving Hypergraphs

    Tony Gracious, Arman Gupta, Ambedkar Dukkipati

  169. On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems

    Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

  170. Heterogeneous Graph Neural Network on Semantic Tree

    Mingyu Guan, Jack W Stokes, Qinlong Luo, Fuchen Liu, Purvanshi Mehta, Elnaz Nouri, Taesoo Kim

  171. Structure-Adaptive Multi-View Graph Clustering for Remote Sensing Data

    Renxiang Guan, Wenxuan Tu, Siwei Wang, Jiyuan Liu, Dayu Hu, Chang Tang, Yu Feng, Junhong Li, Baili Xiao, Xinwang Liu

  172. Enhancing Multivariate Time-Series Domain Adaptation via Contrastive Frequency Graph Discovery and Language-Guided Adversary Alignment

    Haoren Guo, Haiyue Zhu, Jiahui Wang, Prahlad Vadakkepat, Weng Khuen Ho, Tong Heng Lee

  173. Pre-Training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

    Van Thuy Hoang, O-Joun Lee

  174. A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation

    Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Henry Hoffmann

  175. Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection

    Yue Hou, He Zhu, Ruomei Liu, Yingke Su, Jinxiang Xia, Junran Wu, Ke Xu

  176. Large Language Model Meets Graph Neural Network in Knowledge Distillation

    Shengxiang Hu, Guobing Zou, Song Yang, Shiyi Lin, Yanglan Gan, Bofeng Zhang, Yixin Chen

  177. GSDiff: Synthesizing Vector Floorplans via Geometry-enhanced Structural Graph Generation

    Sizhe Hu, Wenming Wu, Yuntao Wang, Benzhu Xu, Liping Zheng

  178. Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection

    Xiaoyu Huang, Weidong Chen, Bo Hu, Zhendong Mao

  179. Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling

    Yongqi Huang, Jitao Zhao, Dongxiao He, Di Jin, Yuxiao Huang, Zhen Wang

  180. SkipPool: Improved Sparse Hierarchical Graph Pooling with Differentiable Exploration

    Sarith Imaduwage

  181. Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning

    Junghun Kim, Ka Hyun Park, Hoyoung Yoon, U Kang

  182. Crossfire: An Elastic Defense Framework for Graph Neural Networks Under Bit Flip Attacks

    Lorenz Kummer, Samir Moustafa, Wilfried Gansterer, Nils Morten Kriege

  183. CG-TGAN: Conditional Generative Adversarial Networks with Graph Neural Networks for Tabular Data Synthesizing

    Seungcheol Lee, Moohong Min

  184. FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning

    Daoyuan Li, Zuyuan Yang, Shengli Xie

  185. Destroy and Repair Using Hyper-Graphs for Routing

    Ke Li, Fei Liu, Zhenkun Wang, Qingfu Zhang

  186. When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline

    Ming Li, Yongchun Gu, Yi Wang, Yujie Fang, Lu Bai, Xiaosheng Zhuang, Pietro Liò

  187. Deep Hypergraph Neural Networks with Tight Framelets

    Ming Li, Yujie Fang, Yi Wang, Han Feng, Yongchun Gu, Lu Bai, Pietro Liò

  188. Community-Centric Graph Unlearning

    Yi Li, Shichao Zhang, Guixian Zhang, Debo Cheng

  189. Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model

    Yujun Li, Hongyuan Zhang, Yuan Yuan

  190. Noise-Injected Spiking Graph Convolution for Energy-Efficient 3D Point Cloud Denoising

    Zikuan Li, Qiaoyun Wu, Jialin Zhang, Kaijun Zhang, Jun Wang

  191. GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning

    Jianqing Liang, Xinkai Wei, Min Chen, Zhiqiang Wang, Jiye Liang

  192. Towards Scalable and Deep Graph Neural Networks via Noise Masking

    Yuxuan Liang, Wentao Zhang, Zeang Sheng, Ling Yang, Quanqing Xu, Jiawei Jiang, Yunhai Tong, Bin Cui

  193. Learning Local Neighborhoods of Non-Gaussian Graphical Models

    Sarah Liaw, Rebecca Morrison, Youssef Marzouk, Ricardo Baptista

  194. Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience

    Ao Liu, Wenshan Li, Tao Li, Beibei Li, Guangquan Xu, Pan Zhou, Wengang Ma, Hanyuan Huang

  195. Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending Against Poisoning Attacks

    Ao Liu, Wenshan Li, Beibei Li, Wengang Ma, Tao Li, Pan Zhou

  196. Subgraph Aggregation for Out-of-Distribution Generalization on Graphs

    Bowen Liu, Haoyang Li, Shuning Wang, Shuo Nie, Shanghang Zhang

  197. Asymmetric Learning for Spectral Graph Neural Networks

    Fangbing Liu, Qing Wang

  198. Federated Graph-Level Clustering Network

    Jingxin Liu, Jieren Cheng, Renda Han, Wenxuan Tu, Jiaxin Wang, Xin Peng

  199. AeroGTO: An Efficient Graph-Transformer Operator for Learning Large-Scale Aerodynamics of 3D Vehicle Geometries

    Pengwei Liu, Pengkai Wang, Xingyu Ren, Hangjie Yuan, Zhongkai Hao, Chao Xu, Shengze Cai, Dong Ni

  200. Fine-Grained Graph Representation Learning for Heterogeneous Mobile Networks with Attentive Fusion and Contrastive Learning

    Shengheng Liu, Tianqi Zhang, Ningning Fu, Yongming Huang

  201. Integrating Co-Training with Edge Discrimination to Enhance Graph Neural Networks Under Heterophily

    Siqi Liu, Dongxiao He, Zhizhi Yu, Di Jin, Zhiyong Feng, Weixiong Zhang

  202. AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic Images

    Yihang Liu, Lianghua He, Ying Wen, Longzhen Yang, Hongzhou Chen

  203. A Simple Graph Contrastive Learning Framework for Short Text Classification

    Yonghao Liu, Fausto Giunchiglia, Lan Huang, Ximing Li, Xiaoyue Feng, Renchu Guan

  204. Adversarial Contrastive Graph Augmentation with Counterfactual Regularization

    Tao Long, Lei Zhang, Liang Zhang, Laizhong Cui

  205. AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification

    Weigang Lu, Ziyu Guan, Wei Zhao, Yaming Yang, Yibing Zhan, Yiheng Lu, Dapeng Tao

  206. Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness

    Agathe Fernandes Machado, Arthur Charpentier, Ewen Gallic

  207. TabGLM: Tabular Graph Language Model for Learning Transferable Representations Through Multi-Modal Consistency Minimization

    Anay Majee, Maria Xenochristou, Wei-Peng Chen

  208. HyperDefender: A Robust Framework for Hyperbolic GNNs

    Nikita Malik, Rahul Gupta, Sandeep Kumar

  209. Causal Inference over Visual-Semantic-Aligned Graph for Image Classification

    Lei Meng, Xiangxian Li, Xiaoshuo Yan, Haokai Ma, Zhuang Qi, Wei Wu, Xiangxu Meng

  210. ID-GMLM: Intelligent Decision-Making with Integrated Graph Models and Large Language Models

    Zhenhua Meng, Fanshen Meng, Rongheng Lin, Budan Wu

  211. AutoSGNN: Automatic Propagation Mechanism Discovery for Spectral Graph Neural Networks

    Shibing Mo, Kai Wu, Qixuan Gao, Xiangyi Teng, Jing Liu

  212. GLAD: Improving Latent Graph Generative Modeling with Simple Quantization

    Van Khoa Nguyen, Yoann Boget, Frantzeska Lavda, Alexandros Kalousis

  213. SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning

    Tianhao Peng, Xuhong Li, Haitao Yuan, Yuchen Li, Haoyi Xiong

  214. DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification

    Feifei Qian, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu, Hangyuan Du, Edwin Hancock

  215. Advancing Retrosynthesis with Retrieval-Augmented Graph Generation

    Anjie Qiao, Zhen Wang, Jiahua Rao, Yuedong Yang, Zhewei Wei

  216. A Scalable and Effective Alternative to Graph Transformers

    Kaan Sancak, Zhigang Hua, Jin Fang, Yan Xie, Andrey Malevich, Bo Long, Muhammed Fatih Balin, Ümit V. Çatalyürek

  217. Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy

    Hyunjin Seo, Kyusung Seo, Joonhyung Park, Eunho Yang

  218. Open-Set Cross-Network Node Classification via Unknown-Excluded Adversarial Graph Domain Alignment

    Xiao Shen, Zhihao Chen, Shirui Pan, Shuang Zhou, Laurence T. Yang, Xi Zhou

  219. Higher Order Structures for Graph Explanations

    Akshit Sinha, Sreeram Vennam, Charu Sharma, Ponnurangam Kumaraguru

  220. Exploring Rationale Learning for Continual Graph Learning

    Lei Song, Jiaxing Li, Qinghua Si, Shihan Guan, Youyong Kong

  221. Temporal-Aware Evaluation and Learning for Temporal Graph Neural Networks

    Junwei Su, Shan Wu

  222. Graph Consistency and Diversity Measurement for Federated Multi-View Clustering

    Bohang Sun, Yongjian Deng, Yuena Lin, Qiuru Hai, Zhen Yang, Gengyu Lyu

  223. Single-View Graph Contrastive Learning with Soft Neighborhood Awareness

    Qingqiang Sun, Chaoqi Chen, Ziyue Qiao, Xubin Zheng, Kai Wang

  224. HyperMixer: Specializable Hypergraph Channel Mixing for Long-term Multivariate Time Series Forecasting

    Changyuan Tian, Zhicong Lu, Zequn Zhang, Heming Yang, Wei Cao, Zhi Guo, Xian Sun, Li Jin

  225. Modeling Inter-Intra Heterogeneity for Graph Federated Learning

    Wentao Yu, Shuo Chen, Yongxin Tong, Tianlong Gu, Chen Gong

  226. Contextual Structure Knowledge Transfer for Graph Neural Networks

    Zhiyuan Yu, Wenzhong Li, Zhangyue Yin, Xiaobin Hong, Shijian Xiao, Sanglu Lu

  227. DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models

    Haonan Yuan, Qingyun Sun, Zhaonan Wang, Xingcheng Fu, Cheng Ji, Yongjian Wang, Bo Jin, Jianxin Li

  228. Graph Structure Refinement with Energy-based Contrastive Learning

    Xianlin Zeng, Yufeng Wang, Yuqi Sun, Guodong Guo, Wenrui Ding, Baochang Zhang

  229. Unlocking the Potential of Black-box Pre-trained GNNs for Graph Few-shot Learning

    Qiannan Zhang, Shichao Pei, Yuan Fang, Xiangliang Zhang

  230. TGLsta: Low-resource Textual Graph Learning with Semantic and Topological Awareness via LLMs

    Qin Zhang, Xiaowei Li, Ziqi Liu, Xiaochen Fan, Xiaojun Chen, Shirui Pan

  231. Domain Adaptive Unfolded Graph Neural Networks

    Zepeng Zhang, Olga Fink

  232. STraj: Self-training for Bridging the Cross-Geography Gap in Trajectory Prediction

    Zhanwei Zhang, Minghao Chen, Zhihong Gu, Xinkui Zhao, Zheng Yang, Binbin Lin, Deng Cai, Wenxiao Wang

  233. Incomplete and Unpaired Multi-View Graph Clustering with Cross-View Feature Fusion

    Liang Zhao, Ziyue Wang, Xiao Wang, Zhikui Chen, Bo Xu

  234. GraSP: Simple Yet Effective Graph Similarity Predictions

    Haoran Zheng, Jieming Shi, Renchi Yang

  235. FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation

    Pengyang Zhou, Chaochao Chen, Weiming Liu, Xinting Liao, Wenkai Shen, Jiahe Xu, Zhihui Fu, Jun Wang, Wu Wen, Xiaolin Zheng

  236. Speedup Techniques for Switchable Temporal Plan Graph Optimization

    He Jiang, Muhan Lin, Jiaoyang Li

  237. Bridging Training and Execution via Dynamic Directed Graph-Based Communication in Cooperative Multi-Agent Systems

    Zhuohui Zhang, Bin He, Bin Cheng, Gang Li

  238. LightPROF: A Lightweight Reasoning Framework for Large Language Model on Knowledge Graph

    Tu Ao, Yanhua Yu, Yuling Wang, Yang Deng, Zirui Guo, Liang Pang, Pinghui Wang, Tat-Seng Chua, Xiao Zhang, Zhen Cai

  239. Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection

    Kedi Chen, Qin Chen, Jie Zhou, Xinqi Tao, Bowen Ding, Jingwen Xie, Mingchen Xie, Peilong Li, Zheng Feng

  240. Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling

    Xinyue Fang, Zhen Huang, Zhiliang Tian, Minghui Fang, Ziyi Pan, Quntian Fang, Zhihua Wen, Hengyue Pan, Dongsheng Li

  241. FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts

    Yichen Gong, Delong Ran, Jinyuan Liu, Conglei Wang, Tianshuo Cong, Anyu Wang, Sisi Duan, Xiaoyun Wang

  242. AutoFEA: Enhancing AI Copilot by Integrating Finite Element Analysis Using Large Language Models with Graph Neural Networks

    Shifu Hou, Rick Johnson, Ramandeep Makhija, Lingwei Chen, Yanfang Ye

  243. HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding

    Rihui Jin, Yu Li, Guilin Qi, Nan Hu, Yuan-Fang Li, Jiaoyan Chen, Jianan Wang, Yongrui Chen, Dehai Min, Sheng Bi

  244. LAMA-UT: Language Agnostic Multilingual ASR Through Orthography Unification and Language-Specific Transliteration

    Sangmin Lee, Woojin Chung, Hong-Goo Kang

  245. Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge Graph

    Xujian Liang, Zhaoquan Gu

  246. Multi-View Empowered Structural Graph Wordification for Language Models

    Zipeng Liu, Likang Wu, Ming He, Zhong Guan, Hongke Zhao, Nan Feng

  247. Knowledge Editing with Dynamic Knowledge Graphs for Multi-Hop Question Answering

    Yifan Lu, Yigeng Zhou, Jing Li, Yequan Wang, Xuebo Liu, Daojing He, Fangming Liu, Min Zhang

  248. Debate on Graph: A Flexible and Reliable Reasoning Framework for Large Language Models

    Jie Ma, Zhitao Gao, Qi Chai, Wangchun Sun, Pinghui Wang, Hongbin Pei, Jing Tao, Lingyun Song, Jun Liu, Chen Zhang, Lizhen Cui

  249. Promising Multi-Granularity Linguistic Steganography by Jointing Syntactic and Lexical Manipulations

    Chengfu Ou, Lingyun Xiang, Yangfan Liu

  250. A Systematic Exploration of Knowledge Graph Alignment with Large Language Models in Retrieval Augmented Generation

    Shiyu Tian, Shuyue Xing, Xingrui Li, Yangyang Luo, Caixia Yuan, Wei Chen, Huixing Jiang, Xiaojie Wang

  251. STLC-KG:A Social Text Steganalysis Method Combining Large-Scale Language Models and Common-Sense Knowledge Graphs

    Zhuang Wang, Linna Zhou, Xuekai Chen, Zhili Zhou, Zhongliang Yang

  252. Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation

    Derong Xu, Xinhang Li, Ziheng Zhang, Zhenxi Lin, Zhihong Zhu, Zhi Zheng, Xian Wu, Xiangyu Zhao, Tong Xu, Enhong Chen

  253. Mixture of Knowledge Minigraph Agents for Literature Review Generation

    Zhi Zhang, Yan Liu, Sheng-hua Zhong, Gong Chen, Yu Yang, Jiannong Cao

  254. SongSong: A Time Phonograph for Chinese SongCi Music from Thousand of Years Away

    Jiliang Hu, Jiajia Li, Ziyi Pan, Chong Chen, Zuchao Li, Ping Wang, Lefei Zhang

  255. Practicable Black-Box Evasion Attacks on Link Prediction in Dynamic Graphs—a Graph Sequential Embedding Method

    Jiate Li, Meng Pang, Binghui Wang

  256. Provably Secure Image Robust Steganography via Cross-modal Error Correction

    Yuang Qi, Kejiang Chen, Na Zhao, Zijin Yang, Weiming Zhang

  257. How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs

    Argyrios Deligkas, Michelle Döring, Eduard Eiben, Tiger-Lily Goldsmith, George Skretas, Georg Tennigkeit

  258. State Encodings for GNN-Based Lifted Planners

    Rostislav Horčik, Gustav Šír, Vítězslav Šimek, Tomáš Pevný

  259. Toward Falsifying Causal Graphs Using a Permutation-Based Test

    Elias Eulig, Atalanti A. Mastakouri, Patrick Blöbaum, Michaela Hardt, Dominik Janzing

  260. Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding

    Simon Ferreira, Charles K. Assaad

  261. Pre-Assignment Problem for Unique Minimum Vertex Cover on Bounded Clique-Width Graphs

    Shinwoo An, Yeonsu Chang, Kyungjin Cho, O-Joung Kwon, Myounghwan Lee, Eunjin Oh, Hyeonjun Shin

  262. Learn2Aggregate: Supervised Generation of Chvatal-Gomory Cuts Using Graph Neural Networks

    Arnaud Deza, Elias B. Khalil, Zhenan Fan, Zirui Zhou, Yong Zhang

  263. Balanced Adaptive Subspace Collaboration for Mixed Pareto-Lexicographic Multi-Objective Problems with Priority Levels

    Wenjing Hong

IJCAI-2024

  1. Contrastive General Graph Matching with Adaptive Augmentation Sampling

    Jianyuan Bo, Yuan Fang

  2. Graph Contrastive Learning with Reinforcement Augmentation

    Ziyang Liu, Chaokun Wang, Cheng Wu

  3. Explore Internal and External Similarity for Single Image Deraining with Graph Neural Networks

    Cong Wang, Wei Wang, Chengjin Yu, Jie Mu

  4. Efficient Tuning and Inference for Large Language Models on Textual Graphs

    Yun Zhu, Yaoke Wang, Haizhou Shi, Siliang Tang

  5. MLP-DINO: Category Modeling and Query Graphing with Deep MLP for Object Detection

    Guiping Cao, Wenjian Huang, Xiangyuan Lan, Jianguo Zhang, Dongmei Jiang, Yaowei Wang

  6. LLM-based Multi-Level Knowledge Generation for Few-shot Knowledge Graph Completion

    Qian Li, Zhuo Chen, Cheng Ji, Shiqi Jiang, Jianxin Li

  7. A Multi-Valued Decision Diagram-Based Approach to Constrained Optimal Path Problems over Directed Acyclic Graphs

    Mingwei Zhang, Liangda Fang, Zhenhao Gu, Quanlong Guan, Yong Lai

  8. Graph Collaborative Expert Finding with Contrastive Learning

    Qiyao Peng, Wenjun Wang, Hongtao Liu, Cuiying Huo, Minglai Shao

  9. Hierarchical Reinforcement Learning on Multi-Channel Hypergraph Neural Network for Course Recommendation

    Lu Jiang, Yanan Xiao, Xinxin Zhao, Yuanbo Xu, Shuli Hu, Pengyang Wang, Minghao Yin

  10. LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning

    Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-Feng Li

  11. Temporal Inductive Logic Reasoning over Hypergraphs

    Yuan Yang, Siheng Xiong, Ali Payani, James C. Kerce, Faramarz Fekri

  12. Toward a Manifold-Preserving Temporal Graph Network in Hyperbolic Space

    Viet Quan Le, Viet Cuong Ta

  13. Sparse Multi-Relational Graph Convolutional Network for Multi-type Object Trajectory Prediction

    Jianhui Zhang, Jun Yao, Liqi Yan, Yanhong Xu, Zheng Wang

  14. Optimal Graph Learning and Nuclear Norm Maximization for Deep Cross-Domain Robust Label Propagation

    Wei Wang, Hanyang Li, Ke Shi, Chao Huang, Yang Cao, Cong Wang, Xiaochun Cao

  15. FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning

    Yinlin Zhu, Xunkai Li, Zhengyu Wu, Di Wu, Miao Hu, Rong-Hua Li

  16. Subgraph Pooling: Tackling Negative Transfer on Graphs

    Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

  17. Kernel Readout for Graph Neural Networks

    Jiajun Yu, Zhihao Wu, Jinyu Cai, Adele Lu Jia, Jicong Fan

  18. HeterGCL: Graph Contrastive Learning Framework on Heterophilic Graph

    Chenhao Wang, Yong Liu, Yan Yang, Wei Li

  19. Hypergraph Self-supervised Learning with Sampling-efficient Signals

    Fan Li, Xiaoyang Wang, Dawei Cheng, Wenjie Zhang, Ying Zhang, Xuemin Lin

  20. Predictive Modeling with Temporal Graphical Representation on Electronic Health Records

    Jiayuan Chen, Changchang Yin, Yuanlong Wang, Ping Zhang

  21. EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost

    Jaeseung Heo, Seungbeom Lee, Sungsoo Ahn, Dongwoo Kim

  22. Multi-Granularity Graph-Convolution-Based Method for Weakly Supervised Person Search

    Haichun Tai, De Cheng, Jie Li, Nannan Wang, Xinbo Gao

  23. AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers

    Wenhao Zhu, Guojie Song, Liang Wang, Shaoguo Liu

  24. A Complete Landscape of EFX Allocations on Graphs: Goods, Chores and Mixed Manna

    Yu Zhou, Tianze Wei, Minming Li, Bo Li

  25. A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

    Sin-Yee Yap, Junn Yong Loo, Chee-Ming Ting, Fuad Noman, Raphaël C.-W. Phan, Adeel Razi, David L. Dowe

  26. Graph Attention Network with High-Order Neighbor Information Propagation for Social Recommendation

    Fei Xiong, Haoran Sun, Guixun Luo, Shirui Pan, Meikang Qiu, Liang Wang

  27. An Efficient Prototype-Based Clustering Approach for Edge Pruning in Graph Neural Networks to Battle Over-Smoothing

    Yuyang Huang, Wenjing Lu, Yang Yang

  28. FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning

    Yi Xu, Ying Li, Haoyu Luo, Xiaoliang Fan, Xiao Liu

  29. Temporal Knowledge Graph Extrapolation via Causal Subhistory Identification

    Kai Chen, Ye Wang, Xin Song, Siwei Chen, Han Yu, Aiping Li

  30. Fast and Continual Knowledge Graph Embedding via Incremental LoRA

    Jiajun Liu, Wenjun Ke, Peng Wang, Jiahao Wang, Jinhua Gao, Ziyu Shang, Guozheng Li, Zijie Xu, Ke Ji, Yining Li

  31. Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations

    Ziqiao Meng, Liang Zeng, Zixing Song, Tingyang Xu, Peilin Zhao, Irwin King

  32. Guidance Graph Optimization for Lifelong Multi-Agent Path Finding

    Yulun Zhang, He Jiang, Varun Bhatt, Stefanos Nikolaidis, Jiaoyang Li

  33. Capturing Knowledge Graphs and Rules with Octagon Embeddings

    Victor Charpenay, Steven Schockaert

  34. CPa-WAC: Constellation Partitioning-based Scalable Weighted Aggregation Composition for Knowledge Graph Embedding

    Sudipta Modak, Aakarsh Malhotra, Sarthak Malik, Anil Surisetty, Esam Abdel-Raheem

  35. Exploring the Role of Node Diversity in Directed Graph Representation Learning

    Jincheng Huang, Yujie Mo, Ping Hu, Xiaoshuang Shi, Shangbo Yuan, Zeyu Zhang, Xiaofeng Zhu

  36. An Image-enhanced Molecular Graph Representation Learning Framework

    Hongxin Xiang, Shuting Jin, Jun Xia, Man Zhou, Jianmin Wang, Li Zeng, Xiangxiang Zeng

  37. Dynamic Weighted Graph Fusion for Deep Multi-View Clustering

    Yazhou Ren, Jingyu Pu, Chenhang Cui, Yan Zheng, Xinyue Chen, Xiaorong Pu, Lifang He

  38. DiffStega: Towards Universal Training-Free Coverless Image Steganography with Diffusion Models

    Yiwei Yang, Zheyuan Liu, Jun Jia, Zhongpai Gao, Yunhao Li, Wei Sun, Xiaohong Liu, Guangtao Zhai

  39. KG-CoT: Chain-of-Thought Prompting of Large Language Models over Knowledge Graphs for Knowledge-Aware Question Answering

    Ruilin Zhao, Feng Zhao, Long Wang, Xianzhi Wang, Guandong Xu

  40. Unsupervised Deep Graph Structure and Embedding Learning

    Xiaobo Shen, Lei Shi, Xiuwen Gong, Shirui Pan

  41. Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning

    Wei Duan, Jie Lu, Junyu Xuan

  42. Make Bricks with a Little Straw: Large-Scale Spatio-Temporal Graph Learning with Restricted GPU-Memory Capacity

    Binwu Wang, Pengkun Wang, Zhengyang Zhou, Zhe Zhao, Wei Xu, Yang Wang

  43. DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives

    Leilei Ding, Dazhong Shen, Chao Wang, Tianfu Wang, Le Zhang, Yanyong Zhang

  44. Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction

    Yicheng Zhou, Pengfei Wang, Hao Dong, Denghui Zhang, Dingqi Yang, Yanjie Fu, Pengyang Wang

  45. Generalized Taxonomy-Guided Graph Neural Networks

    Yu Zhou, Di Jin, Jianguo Wei, Dongxiao He, Zhizhi Yu, Weixiong Zhang

  46. Dual Contrastive Graph-Level Clustering with Multiple Cluster Perspectives Alignment

    Jinyu Cai, Yunhe Zhang, Jicong Fan, Yali Du, Wenzhong Guo

  47. Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting

    Xi Chen, Chuan Qin, Zhigaoyuan Wang, Yihang Cheng, Chao Wang, Hengshu Zhu, Hui Xiong

  48. LG-GNN: Local-Global Adaptive Graph Neural Network for Modeling Both Homophily and Heterophily

    Zhizhi Yu, Bin Feng, Dongxiao He, Zizhen Wang, Yuxiao Huang, Zhiyong Feng

  49. Integrating Vision-Language Semantic Graphs in Multi-View Clustering

    JunLong Ke, Zichen Wen, Yechenhao Yang, Chenhang Cui, Yazhou Ren, Xiaorong Pu, Lifang He

  50. Learning Multi-Granularity and Adaptive Representation for Knowledge Graph Reasoning

    Ziyu Shang, Peng Wang, Wenjun Ke, Jiajun Liu, Hailang Huang, Guozheng Li, Chenxiao Wu, Jianghan Liu, Xiye Chen, Yining Li

  51. WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction

    Binqing Wu, Weiqi Chen, Wengwei Wang, Bingqing Peng, Liang Sun, Ling Chen

  52. Heterogeneous Graph Transformer with Poly-Tokenization

    Zhiyuan Lu, Yuan Fang, Cheng Yang, Chuan Shi

  53. Temporal Graph ODEs for Irregularly-Sampled Time Series

    Alessio Gravina, Daniele Zambon, Davide Bacciu, Cesare Alippi

  54. Joint Domain Adaptive Graph Convolutional Network

    Niya Yang, Ye Wang, Zhizhi Yu, Dongxiao He, Xin Huang, Di Jin

  55. A Logic for Reasoning about Aggregate-Combine Graph Neural Networks

    Pierre Nunn, Marco Sälzer, François Schwarzentruber, Nicolas Troquard

  56. Faster Optimal Coalition Structure Generation via Offline Coalition Selection and Graph-Based Search

    Redha Taguelmimt, Samir Aknine, Djamila Boukredera, Narayan Changder, Tuomas Sandholm

  57. Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

    Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera Paredes, Petar Veličković, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner

  58. Rethinking the Effectiveness of Graph Classification Datasets in Benchmarks for Assessing GNNs

    Zhengdao Li, Yong Cao, Kefan Shuai, Yiming Miao, Kai Hwang

  59. Layered Graph Security Games

    Jakub Cerny, Chun Kai Ling, Christian Kroer, Garud Iyengar

  60. A Graph-based Representation Framework for Trajectory Recovery via Spatiotemporal Interval-Informed Seq2Seq

    Yaya Zhao, Kaiqi Zhao, Zhiqian Chen, Yuanyuan Zhang, Yalei Du, Xiaoling Lu

  61. MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction

    Wenjie Du, Shuai Zhang, Di Wu, Jun Xia, Ziyuan Zhao, Junfeng Fang, Yang Wang

  62. Deep Hierarchical Graph Alignment Kernels

    Shuhao Tang, Hao Tian, Xiaofeng Cao, Wei Ye

  63. Multi-Relational Graph Attention Network for Social Relationship Inference from Human Mobility Data

    Guangming Qin, Jianpeng Qi, Bin Wang, Guiyuan Jiang, Yanwei Yu, Junyu Dong

  64. Gradformer: Graph Transformer with Exponential Decay

    Chuang Liu, Zelin Yao, Yibing Zhan, Xueqi Ma, Shirui Pan, Wenbin Hu

  65. Rank and Align: Towards Effective Source-free Graph Domain Adaptation

    Junyu Luo, Zhiping Xiao, Yifan Wang, Xiao Luo, Jingyang Yuan, Wei Ju, Langechuan Liu, Ming Zhang

  66. A General Black-box Adversarial Attack on Graph-based Fake News Detectors

    Peican Zhu, Zechen Pan, Yang Liu, Jiwei Tian, Keke Tang, Zhen Wang

  67. History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting

    Julia Gastinger, Christian Meilicke, Federico Errica, Timo Sztyler, Anett Schülke, Heiner Stuckenschmidt

  68. DGCD: An Adaptive Denoising GNN for Group-level Cognitive Diagnosis

    Haiping Ma, Siyu Song, Chuan Qin, Xiaoshan Yu, Limiao Zhang, Xingyi Zhang, Hengshu Zhu

  69. Enhancing Multimodal Knowledge Graph Representation Learning through Triple Contrastive Learning

    Yuxing Lu, Weichen Zhao, Nan Sun, Jinzhuo Wang

  70. Heterogeneous Causal Metapath Graph Neural Network for Gene-Microbe-Disease Association Prediction

    Kexin Zhang, Feng Huang, Luotao Liu, Zhankun Xiong, Hongyu Zhang, Yuan Quan, Wen Zhang

  71. A Context-Enhanced Framework for Sequential Graph Reasoning

    Shuo Shi, Chao Peng, Chenyang Xu, Zhengfeng Yang

  72. FairGT: A Fairness-aware Graph Transformer

    Renqiang Luo, Huafei Huang, Shuo Yu, Xiuzhen Zhang, Feng Xia

  73. Dynamicity-aware Social Bot Detection with Dynamic Graph Transformers

    Buyun He, Yingguang Yang, Qi Wu, Hao Liu, Renyu Yang, Hao Peng, Xiang Wang, Yong Liao, Pengyuan Zhou

  74. Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders

    Chuang Liu, Yuyao Wang, Yibing Zhan, Xueqi Ma, Dapeng Tao, Jia Wu, Wenbin Hu

  75. Anomaly Subgraph Detection through High-Order Sampling Contrastive Learning

    Ying Sun, Wenjun Wang, Nannan Wu, Chunlong Bao

  76. ScreenAI: A Vision-Language Model for UI and Infographics Understanding

    Gilles Baechler, Srinivas Sunkara, Maria Wang, Fedir Zubach, Hassan Mansoor, Vincent Etter, Victor Carbune, Jason Lin, Jindong Chen, Abhanshu Sharma

  77. Practical Anytime Algorithms for Judicious Partitioning of Active Directory Attack Graphs

    Yumeng Zhang, Max Ward, Hung Nguyen

  78. LG-FGAD: An Effective Federated Graph Anomaly Detection Framework

    Jinyu Cai, Yunhe Zhang, Jicong Fan, See-Kiong Ng

  79. Multiplex Graph Representation Learning via Bi-level Optimization

    Yudi Huang, Yujie Mo, Yujing Liu, Ci Nie, Guoqiu Wen, Xiaofeng Zhu

  80. Robust Heterophilic Graph Learning against Label Noise for Anomaly Detection

    Junhang Wu, Ruimin Hu, Dengshi Li, Zijun Huang, Lingfei Ren, Yilong Zang

  81. Efficient Correlated Subgraph Searches for AI-powered Drug Discovery

    Hiroaki Shiokawa, Yuma Naoi, Shohei Matsugu

  82. Continual Multimodal Knowledge Graph Construction

    Xiang Chen, Jingtian Zhang, Xiaohan Wang, Ningyu Zhang, Tongtong Wu, Yuxiang Wang, Yongheng Wang, Huajun Chen

ICML-2024

  1. Less is More: on the Over-Globalizing Problem in Graph Transformers.

    Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi

  2. Expressivity and Generalization: Fragment-Biases for Molecular GNNs.

    Tom Wollschläger, Niklas Kemper, Leon Hetzel, Johanna Sommer, Stephan Günnemann

  3. From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble.

    Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye

  4. Multiplicative Weights Update, Area Convexity and Random Coordinate Descent for Densest Subgraph Problems.

    Ta Duy Nguyen, Alina Ene

  5. LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering.

    Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu

  6. EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction.

    Yang Zhang, Zhewei Wei, Ye Yuan, Chongxuan Li, Wenbing Huang

  7. GPTSwarm: Language Agents as Optimizable Graphs.

    Mingchen Zhuge, Wenyi Wang, Louis Kirsch, Francesco Faccio, Dmitrii Khizbullin, Jürgen Schmidhuber

  8. Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing.

    Hongbin Pei, Yu Li, Huiqi Deng, Jingxin Hai, Pinghui Wang, Jie Ma, Jing Tao, Yuheng Xiong, Xiaohong Guan

  9. Position: Graph Foundation Models Are Already Here.

    Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang

  10. Pairwise Alignment Improves Graph Domain Adaptation.

    Shikun Liu, Deyu Zou, Han Zhao, Pan Li

  11. Stereographic Spherical Sliced Wasserstein Distances.

    Huy Tran, Yikun Bai, Abihith Kothapalli, Ashkan Shahbazi, Xinran Liu, Rocio Diaz Martin, Soheil Kolouri

  12. QBMK: Quantum-based Matching Kernels for Un-attributed Graphs.

    Lu Bai, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock

  13. Individual Fairness in Graph Decomposition.

    Kamesh Munagala, Govind S. Sankar

  14. An Efficient Maximal Ancestral Graph Listing Algorithm.

    Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou

  15. Graph-Triggered Rising Bandits.

    Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni, Alberto Maria Metelli

  16. DUPLEX: Dual GAT for Complex Embedding of Directed Graphs.

    Zhaoru Ke, Hang Yu, Jianguo Li, Haipeng Zhang

  17. Graph Distillation with Eigenbasis Matching.

    Yang Liu, Deyu Bo, Chuan Shi

  18. Recurrent Distance Filtering for Graph Representation Learning.

    Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann

  19. Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization.

    Haoyang Li, Xin Wang, Zeyang Zhang, Haibo Chen, Ziwei Zhang, Wenwu Zhu

  20. Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model.

    Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka

  21. Effective Federated Graph Matching.

    Yang Zhou, Zijie Zhang, Zeru Zhang, Lingjuan Lyu, Wei-Shinn Ku

  22. Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks.

    Haoyu Li, Shichang Zhang, Longwen Tang, Mathieu Bauchy, Yizhou Sun

  23. Explaining Graph Neural Networks via Structure-aware Interaction Index.

    Ngoc Bui, Hieu Trung Nguyen, Viet Anh Nguyen, Rex Ying

  24. Graph Structure Extrapolation for Out-of-Distribution Generalization.

    Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji

  25. Understanding Heterophily for Graph Neural Networks.

    Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

  26. Quantum Positional Encodings for Graph Neural Networks.

    Slimane Thabet, Mehdi Djellabi, Igor Olegovich Sokolov, Sachin Kasture, Louis-Paul Henry, Loïc Henriet

  27. Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation.

    Kartik Sharma, Srijan Kumar, Rakshit Trivedi

  28. Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph.

    Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu, Jianye Hao, Feng Wu

  29. The Expressive Power of Path-Based Graph Neural Networks.

    Caterina Graziani, Tamara Drucks, Fabian Jogl, Monica Bianchini, Franco Scarselli, Thomas Gärtner

  30. Graph Neural Networks with a Distribution of Parametrized Graphs.

    See Hian Lee, Feng Ji, Kelin Xia, Wee Peng Tay

  31. Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning.

    Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan

  32. Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS.

    Amir Azarmehr, Soheil Behnezhad, Mohammad Roghani

  33. Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks.

    Haixiao Wang, Zhichao Wang

  34. Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning.

    Dongkwan Kim, Alice Oh

  35. Unsupervised Episode Generation for Graph Meta-learning.

    Jihyeong Jung, Sangwoo Seo, Sungwon Kim, Chanyoung Park

  36. Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs.

    Moonjeong Park, Jaeseung Heo, Dongwoo Kim

  37. On the Expressive Power of Spectral Invariant Graph Neural Networks.

    Bohang Zhang, Lingxiao Zhao, Haggai Maron

  38. Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers.

    Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian

  39. Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach.

    Weijia Zhang, Chenlong Yin, Hao Liu, Xiaofang Zhou, Hui Xiong

  40. CKGConv: General Graph Convolution with Continuous Kernels.

    Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates

  41. Hyperbolic Geometric Latent Diffusion Model for Graph Generation.

    Xingcheng Fu, Yisen Gao, Yuecen Wei, Qingyun Sun, Hao Peng, Jianxin Li, Xianxian Li

  42. VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context.

    Yunxin Li, Baotian Hu, Haoyuan Shi, Wei Wang, Longyue Wang, Min Zhang

  43. Large Language Models are Geographically Biased.

    Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, Stefano Ermon

  44. MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models.

    Justin Chih-Yao Chen, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal

  45. Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm.

    Fuzhong Zhou, Chenyu Zhang, Xu Chen, Xuan Di

  46. Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering.

    Mitchell Black, Lucy Lin, Weng-Keen Wong, Amir Nayyeri

  47. Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning.

    Yuelin Zhang, Jiacheng Cen, Jiaqi Han, Zhiqiang Zhang, Jun Zhou, Wenbing Huang

  48. Graph Geometry-Preserving Autoencoders.

    Jungbin Lim, Jihwan Kim, Yonghyeon Lee, Cheongjae Jang, Frank C. Park

  49. Graph2Tac: Online Representation Learning of Formal Math Concepts.

    Lasse Blaauwbroek, Mirek Olsák, Jason Rute, Fidel Ivan Schaposnik Massolo, Jelle Piepenbrock, Vasily Pestun

  50. Cooperative Graph Neural Networks.

    Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, Ismail Ilkan Ceylan

  51. Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling.

    Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi

  52. MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation.

    Alexandre Hayderi, Amin Saberi, Ellen Vitercik, Anders Wikum

  53. Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning.

    Konstantinos Ameranis, Adela Frances DePavia, Lorenzo Orecchia, Erasmo Tani

  54. What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding.

    Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen

  55. Homomorphism Counts for Graph Neural Networks: All About That Basis.

    Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger

  56. Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks.

    Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro

  57. Efficient Contextual Bandits with Uninformed Feedback Graphs.

    Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro

  58. HAMLET: Graph Transformer Neural Operator for Partial Differential Equations.

    Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero

  59. Uncertainty for Active Learning on Graphs.

    Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier, Antonio Oroz, Stephan Günnemann

  60. Comparing Graph Transformers via Positional Encodings.

    Mitchell Black, Zhengchao Wan, Gal Mishne, Amir Nayyeri, Yusu Wang

  61. Graph Positional and Structural Encoder.

    Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek

  62. Long Range Propagation on Continuous-Time Dynamic Graphs.

    Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt

  63. Simulation of Graph Algorithms with Looped Transformers.

    Artur Back de Luca, Kimon Fountoulakis

  64. Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting.

    Andrea Cini, Danilo P. Mandic, Cesare Alippi

  65. Robust Inverse Graphics via Probabilistic Inference.

    Tuan Anh Le, Pavel Sountsov, Matthew Douglas Hoffman, Ben Lee, Brian Patton, Rif A. Saurous

  66. Editing Partially Observable Networks via Graph Diffusion Models.

    Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra

  67. Learning in Deep Factor Graphs with Gaussian Belief Propagation.

    Seth Nabarro, Mark van der Wilk, Andrew J. Davison

  68. Generalized Sobolev Transport for Probability Measures on a Graph.

    Tam Le, Truyen Nguyen, Kenji Fukumizu

  69. Learning Graph Representation via Graph Entropy Maximization.

    Ziheng Sun, Xudong Wang, Chris Ding, Jicong Fan

  70. Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks.

    Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mondal, Hua Wei, Dongsheng Luo

  71. EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs.

    Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou

  72. Modelling Microbial Communities with Graph Neural Networks.

    Albane Ruaud, Cansu Sancaktar, Marco Bagatella, Christoph Ratzke, Georg Martius

  73. Community-Invariant Graph Contrastive Learning.

    Shiyin Tan, Dongyuan Li, Renhe Jiang, Ying Zhang, Manabu Okumura

  74. Probabilistic Routing for Graph-Based Approximate Nearest Neighbor Search.

    Kejing Lu, Chuan Xiao, Yoshiharu Ishikawa

  75. SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter.

    Haobo Xu, Yuchen Yan, Dingsu Wang, Zhe Xu, Zhichen Zeng, Tarek F. Abdelzaher, Jiawei Han, Hanghang Tong

  76. Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective.

    Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin

  77. Graph-enhanced Large Language Models in Asynchronous Plan Reasoning.

    Fangru Lin, Emanuele La Malfa, Valentin Hofmann, Elle Michelle Yang, Anthony G. Cohn, Janet B. Pierrehumbert

  78. Structure Your Data: Towards Semantic Graph Counterfactuals.

    Angeliki Dimitriou, Maria Lymperaiou, Giorgos Filandrianos, Konstantinos Thomas, Giorgos Stamou

  79. HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming.

    Yang Wu, Yifan Zhang, Zhenxing Liang, Jian Cheng

  80. Efficient Contrastive Learning for Fast and Accurate Inference on Graphs.

    Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar

  81. An Empirical Study of Realized GNN Expressiveness.

    Yanbo Wang, Muhan Zhang

  82. S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning.

    Guancheng Wan, Yijun Tian, Wenke Huang, Nitesh V. Chawla, Mang Ye

  83. On the Role of Edge Dependency in Graph Generative Models.

    Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis

  84. Graph Neural Network Explanations are Fragile.

    Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang

  85. GNNs Also Deserve Editing, and They Need It More Than Once.

    Shaochen Zhong, Duy Le, Zirui Liu, Zhimeng Jiang, Andrew Ye, Jiamu Zhang, Jiayi Yuan, Kaixiong Zhou, Zhaozhuo Xu, Jing Ma, Shuai Xu, Vipin Chaudhary, Xia Hu

  86. How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing.

    Keke Huang, Yu Guang Wang, Ming Li, Pietro Lio

  87. Position: Relational Deep Learning - Graph Representation Learning on Relational Databases.

    Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec

  88. Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products.

    Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron

  89. A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering.

    Vincent Cohen-Addad, Tommaso d'Orsi, Aida Mousavifar

  90. ILILT: Implicit Learning of Inverse Lithography Technologies.

    Haoyu Yang, Haoxing Ren

  91. Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction.

    Arjun Subramonian, Levent Sagun, Yizhou Sun

  92. Graph Mixup on Approximate Gromov-Wasserstein Geodesics.

    Zhichen Zeng, Ruizhong Qiu, Zhe Xu, Zhining Liu, Yuchen Yan, Tianxin Wei, Lei Ying, Jingrui He, Hanghang Tong

  93. Rethinking Independent Cross-Entropy Loss For Graph-Structured Data.

    Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang

  94. Sign Rank Limitations for Inner Product Graph Decoders.

    Su Hyeong Lee, Qingqi Zhang, Risi Kondor

  95. Graph External Attention Enhanced Transformer.

    Jianqing Liang, Min Chen, Jiye Liang

  96. Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs.

    Shenzhi Yang, Bin Liang, An Liu, Lin Gui, Xingkai Yao, Xiaofang Zhang

  97. Delaunay Graph: Addressing Over-Squashing and Over-Smoothing Using Delaunay Triangulation.

    Hugo Attali, Davide Buscaldi, Nathalie Pernelle

  98. A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer.

    Zhangyang Gao, Daize Dong, Cheng Tan, Jun Xia, Bozhen Hu, Stan Z. Li

  99. Generalization Error of Graph Neural Networks in the Mean-field Regime.

    Gholamali Aminian, Yixuan He, Gesine Reinert, Lukasz Szpruch, Samuel N. Cohen

  100. Surprisingly Strong Performance Prediction with Neural Graph Features.

    Gabriela Kadlecová, Jovita Lukasik, Martin Pilát, Petra Vidnerová, Mahmoud Safari, Roman Neruda, Frank Hutter

  101. Learning Divergence Fields for Shift-Robust Graph Representations.

    Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan

  102. SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States.

    Noga Mudrik, Gal Mishne, Adam S. Charles

  103. LLaGA: Large Language and Graph Assistant.

    Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang

  104. Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs.

    Langzhang Liang, Sunwoo Kim, Kijung Shin, Zenglin Xu, Shirui Pan, Yuan Qi

  105. Knowledge Graphs Can be Learned with Just Intersection Features.

    Duy Le, Shaochen Zhong, Zirui Liu, Shuai Xu, Vipin Chaudhary, Kaixiong Zhou, Zhaozhuo Xu

  106. Robust Graph Matching when Nodes are Corrupt.

    Taha Ameen, Bruce E. Hajek

  107. Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders.

    Xue Yu, Muchen Li, Yan Leng, Renjie Liao

  108. Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs.

    Slobodan Mitrovic, Theodore Pan

  109. Position: Future Directions in the Theory of Graph Machine Learning.

    Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

  110. Graph Neural PDE Solvers with Conservation and Similarity-Equivariance.

    Masanobu Horie, Naoto Mitsume

  111. Graph Out-of-Distribution Detection Goes Neighborhood Shaping.

    Tianyi Bao, Qitian Wu, Zetian Jiang, Yiting Chen, Jiawei Sun, Junchi Yan

  112. Hypergraph-enhanced Dual Semi-supervised Graph Classification.

    Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang

  113. Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification.

    Xixun Lin, Wenxiao Zhang, Fengzhao Shi, Chuan Zhou, Lixin Zou, Xiangyu Zhao, Dawei Yin, Shirui Pan, Yanan Cao

  114. EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time.

    Shengyao Lu, Bang Liu, Keith G. Mills, Jiao He, Di Niu

  115. On the Generalization of Equivariant Graph Neural Networks.

    Rafal Karczewski, Amauri H. Souza, Vikas Garg

  116. Perfect Alignment May be Poisonous to Graph Contrastive Learning.

    Jingyu Liu, Huayi Tang, Yong Liu

  117. Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective.

    Yang Chen, Cong Fang, Zhouchen Lin, Bing Liu

  118. Graph Automorphism Group Equivariant Neural Networks.

    Edward Pearce-Crump, William J. Knottenbelt

  119. KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning.

    Junnan Liu, Qianren Mao, Weifeng Jiang, Jianxin Li

  120. How Graph Neural Networks Learn: Lessons from Training Dynamics.

    Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan

  121. Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE.

    Hao Wu, Huiyuan Wang, Kun Wang, Weiyan Wang, Changan Ye, Yangyu Tao, Chong Chen, Xian-Sheng Hua, Xiao Luo

  122. StrokeNUWA - Tokenizing Strokes for Vector Graphic Synthesis.

    Zecheng Tang, Chenfei Wu, Zekai Zhang, Minheng Ni, Shengming Yin, Yu Liu, Zhengyuan Yang, Lijuan Wang, Zicheng Liu, Juntao Li, Nan Duan

  123. Collective Certified Robustness against Graph Injection Attacks.

    Yuni Lai, Bailin Pan, Kaihuang Chen, Yancheng Yuan, Kai Zhou

  124. Class-Imbalanced Graph Learning without Class Rebalancing.

    Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong

  125. Graph Adversarial Diffusion Convolution.

    Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu

  126. PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning.

    Jaejun Lee, Minsung Hwang, Joyce Jiyoung Whang

  127. Empowering Graph Invariance Learning with Deep Spurious Infomax.

    Tianjun Yao, Yongqiang Chen, Zhenhao Chen, Kai Hu, Zhiqiang Shen, Kun Zhang

  128. Graph As Point Set.

    Xiyuan Wang, Pan Li, Muhan Zhang

  129. Mitigating Label Noise on Graphs via Topological Sample Selection.

    Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu

  130. Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning.

    Yuhao Wu, Jiangchao Yao, Bo Han, Lina Yao, Tongliang Liu

  131. Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness.

    Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen

  132. Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet.

    Zeyang Zhang, Xin Wang, Yijian Qin, Hong Chen, Ziwei Zhang, Xu Chu, Wenwu Zhu

  133. Graph Generation with Diffusion Mixture.

    Jaehyeong Jo, Dongki Kim, Sung Ju Hwang

  134. Graph Neural Networks Use Graphs When They Shouldn't.

    Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

  135. Exploring Correlations of Self-Supervised Tasks for Graphs.

    Taoran Fang, Wei Chow, Yifei Sun, Kaiqiao Han, Lvbin Ma, Yang Yang

  136. Equivariant Graph Neural Operator for Modeling 3D Dynamics.

    Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar

  137. Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning.

    Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin

  138. How Interpretable Are Interpretable Graph Neural Networks?

    Yongqiang Chen, Yatao Bian, Bo Han, James Cheng

  139. Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency.

    Hyeongjin Kim, Sangwon Kim, Dasom Ahn, Jong Taek Lee, Byoung Chul Ko

  140. Federated Self-Explaining GNNs with Anti-shortcut Augmentations.

    Linan Yue, Qi Liu, Weibo Gao, Ye Liu, Kai Zhang, Yichao Du, Li Wang, Fangzhou Yao

  141. HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network.

    Bor-Jiun Lin, Chun-Yi Lee

  142. Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching.

    Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, Yang You

  143. Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization.

    Rui Li, Chaozhuo Li, Yanming Shen, Zeyu Zhang, Xu Chen

KDD-2024

  1. A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs.

    Amitoz Azad, Yuan Fang

  2. Graph Mamba: Towards Learning on Graphs with State Space Models.

    Ali Behrouz, Farnoosh Hashemi

  3. DiffusionE: Reasoning on Knowledge Graphs via Diffusion-based Graph Neural Networks.

    Zongsheng Cao, Jing Li, Zigan Wang, Jinliang Li

  4. Path-based Explanation for Knowledge Graph Completion.

    Heng Chang, Jiangnan Ye, Alejo Lopez-Avila, Jinhua Du, Jia Li

  5. Scalable Algorithm for Finding Balanced Subgraphs with Tolerance in Signed Networks.

    Jingbang Chen, Qiuyang Mang, Hangrui Zhou, Richard Peng, Yu Gao, Chenhao Ma

  6. QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering.

    Junyang Chen, Yuzhu Ji, Rong Zou, Yiqun Zhang, Yiu-ming Cheung

  7. GraphWiz: An Instruction-Following Language Model for Graph Computational Problems.

    Nuo Chen, Yuhan Li, Jianheng Tang, Jia Li

  8. DyGKT: Dynamic Graph Learning for Knowledge Tracing.

    Ke Cheng, Linzhi Peng, Pengyang Wang, Junchen Ye, Leilei Sun, Bowen Du

  9. Resurrecting Label Propagation for Graphs with Heterophily and Label Noise.

    Yao Cheng, Caihua Shan, Yifei Shen, Xiang Li, Siqiang Luo, Dongsheng Li

  10. Retrieval-Augmented Hypergraph for Multimodal Social Media Popularity Prediction.

    Zhangtao Cheng, Jienan Zhang, Xovee Xu, Goce Trajcevski, Ting Zhong, Fan Zhou

  11. Enhancing Contrastive Learning on Graphs with Node Similarity.

    Hongliang Chi, Yao Ma

  12. Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing.

    Jiajun Cui, Hong Qian, Bo Jiang, Wei Zhang

  13. AGS-GNN: Attribute-guided Sampling for Graph Neural Networks.

    Siddhartha Shankar Das, S. M. Ferdous, Mahantesh M. Halappanavar, Edoardo Serra, Alex Pothen

  14. Unsupervised Alignment of Hypergraphs with Different Scales.

    Manh Tuan Do, Kijung Shin

  15. IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks.

    Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li

  16. Representation Learning of Temporal Graphs with Structural Roles.

    Huaming Du, Long Shi, Xingyan Chen, Yu Zhao, Hegui Zhang, Carl Yang, Fuzhen Zhuang, Gang Kou

  17. Reserving-Masking-Reconstruction Model for Self-Supervised Heterogeneous Graph Representation.

    Haoran Duan, Cheng Xie, Linyu Li

  18. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks.

    Wenying Duan, Tianxiang Fang, Hong Rao, Xiaoxi He

  19. GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models.

    Yi Fang, Dongzhe Fan, Daochen Zha, Qiaoyu Tan

  20. Influence Maximization via Graph Neural Bandits.

    Yuting Feng, Vincent Y. F. Tan, Bogdan Cautis

  21. Federated Graph Learning with Structure Proxy Alignment.

    Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li

  22. Graph Condensation for Open-World Graph Learning.

    Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin

  23. An Energy-centric Framework for Category-free Out-of-distribution Node Detection in Graphs.

    Zheng Gong, Ying Sun

  24. Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective.

    Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang

  25. Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations.

    Linxin Guo, Yaochen Zhu, Min Gao, Yinghui Tao, Junliang Yu, Chen Chen

  26. HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning.

    Zhuoning Guo, Duanyi Yao, Qiang Yang, Hao Liu

  27. Expander Hierarchies for Normalized Cuts on Graphs.

    Kathrin Hanauer, Monika Henzinger, Robin Münk, Harald Räcke, Maximilian Vötsch

  28. A Unified Core Structure in Multiplex Networks: From Finding the Densest Subgraph to Modeling User Engagement.

    Farnoosh Hashemi, Ali Behrouz

  29. RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network.

    Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song

  30. Privacy-Preserved Neural Graph Databases.

    Qi Hu, Haoran Li, Jiaxin Bai, Zihao Wang, Yangqiu Song

  31. Can Modifying Data Address Graph Domain Adaptation?

    Renhong Huang, Jiarong Xu, Xin Jiang, Ruichuan An, Yang Yang

  32. MemMap: An Adaptive and Latent Memory Structure for Dynamic Graph Learning.

    Shuo Ji, Mingzhe Liu, Leilei Sun, Chuanren Liu, Tongyu Zhu

  33. Killing Two Birds with One Stone: Cross-modal Reinforced Prompting for Graph and Language Tasks.

    Wenyuan Jiang, Wenwei Wu, Le Zhang, Zixuan Yuan, Jian Xiang, Jingbo Zhou, Hui Xiong

  34. Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Leman Go Indifferent.

    Lorenz Kummer, Samir Moustafa, Sebastian Schrittwieser, Wilfried N. Gansterer, Nils M. Kriege

  35. Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks.

    Yurui Lai, Xiaoyang Lin, Renchi Yang, Hongtao Wang

  36. Dynamic Neural Dowker Network: Approximating Persistent Homology in Dynamic Directed Graphs.

    Hao Li, Hao Jiang, Jiajun Fan, Dongsheng Ye, Liang Du

  37. Causal Subgraph Learning for Generalizable Inductive Relation Prediction.

    Mei Li, Xiaoguang Liu, Hua Ji, Shuangjia Zheng

  38. SimDiff: Simple Denoising Probabilistic Latent Diffusion Model for Data Augmentation on Multi-modal Knowledge Graph.

    Ran Li, Shimin Di, Lei Chen, Xiaofang Zhou

  39. Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach.

    Yicong Li, Yu Yang, Jiannong Cao, Shuaiqi Liu, Haoran Tang, Guandong Xu

  40. ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs.

    Yuhan Li, Peisong Wang, Zhixun Li, Jeffrey Xu Yu, Jia Li

  41. Rethinking Fair Graph Neural Networks from Re-balancing.

    Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu

  42. Customizing Graph Neural Network for CAD Assembly Recommendation.

    Fengqi Liang, Huan Zhao, Yuhan Quan, Wei Fang, Chuan Shi

  43. When Box Meets Graph Neural Network in Tag-aware Recommendation.

    Fake Lin, Ziwei Zhao, Xi Zhu, Da Zhang, Shitian Shen, Xueying Li, Tong Xu, Suojuan Zhang, Enhong Chen

  44. PSMC: Provable and Scalable Algorithms for Motif Conductance Based Graph Clustering.

    Longlong Lin, Tao Jia, Zeli Wang, Jin Zhao, Rong-Hua Li

  45. Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective.

    Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen

  46. Graph Data Condensation via Self-expressive Graph Structure Reconstruction.

    Zhanyu Liu, Chaolv Zeng, Guanjie Zheng

  47. AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation.

    Weigang Lu, Ziyu Guan, Wei Zhao, Yaming Yang

  48. FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks.

    Renqiang Luo, Huafei Huang, Shuo Yu, Zhuoyang Han, Estrid He, Xiuzhen Zhang, Feng Xia

  49. Cross-Context Backdoor Attacks against Graph Prompt Learning.

    Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang

  50. PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer.

    Jiahong Ma, Mingguo He, Zhewei Wei

  51. Graph Anomaly Detection with Few Labels: A Data-Centric Approach.

    Xiaoxiao Ma, Ruikun Li, Fanzhen Liu, Kaize Ding, Jian Yang, Jia Wu

  52. How Powerful is Graph Filtering for Recommendation.

    Shaowen Peng, Xin Liu, Kazunari Sugiyama, Tsunenori Mine

  53. Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals.

    Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci

  54. Reimagining Graph Classification from a Prototype View with Optimal Transport: Algorithm and Theorem.

    Chen Qian, Huayi Tang, Hong Liang, Yong Liu

  55. A Fast Exact Algorithm to Enumerate Maximal Pseudo-cliques in Large Sparse Graphs.

    Ahsanur Rahman, Kalyan Roy, Ramiza Maliha, Townim Faisal Chowdhury

  56. DPHGNN: A Dual Perspective Hypergraph Neural Networks.

    Siddhant Saxena, Shounak Ghatak, Raghu Kolla, Debashis Mukherjee, Tanmoy Chakraborty

  57. Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck.

    Sangwoo Seo, Sungwon Kim, Jihyeong Jung, Yoonho Lee, Chanyoung Park

  58. NeuroCut: A Neural Approach for Robust Graph Partitioning.

    Rishi Shah, Krishnanshu Jain, Sahil Manchanda, Sourav Medya, Sayan Ranu

  59. Certified Robustness on Visual Graph Matching via Searching Optimal Smoothing Range.

    Huaqing Shao, Lanjun Wang, Yongwei Wang, Qibing Ren, Junchi Yan

  60. Capturing Homogeneous Influence among Students: Hypergraph Cognitive Diagnosis for Intelligent Education Systems.

    Junhao Shen, Hong Qian, Shuo Liu, Wei Zhang, Bo Jiang, Aimin Zhou

  61. Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models.

    Xu Shen, Yili Wang, Kaixiong Zhou, Shirui Pan, Xin Wang

  62. MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline.

    Guangming Sheng, Junwei Su, Chao Huang, Chuan Wu

  63. LPFormer: An Adaptive Graph Transformer for Link Prediction.

    Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang

  64. Fast Computation for the Forest Matrix of an Evolving Graph.

    Haoxin Sun, Xiaotian Zhou, Zhongzhi Zhang

  65. DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization.

    Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang

  66. Self-Supervised Denoising through Independent Cascade Graph Augmentation for Robust Social Recommendation.

    Youchen Sun, Zhu Sun, Yingpeng Du, Jie Zhang, Yew Soon Ong

  67. Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute.

    Tajima Shinji, Ren Sugihara, Ryota Kitahara, Masayuki Karasuyama

  68. HiGPT: Heterogeneous Graph Language Model.

    Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Long Xia, Dawei Yin, Chao Huang

  69. Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning.

    Jiakai Tang, Sunhao Dai, Zexu Sun, Xu Chen, Jun Xu, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li

  70. Latent Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model.

    Yuxing Tian, Aiwen Jiang, Qi Huang, Jian Guo, Yiyan Qi

  71. Flexible Graph Neural Diffusion with Latent Class Representation Learning.

    Liangtian Wan, Huijin Han, Lu Sun, Zixun Zhang, Zhaolong Ning, Xiaoran Yan, Feng Xia

  72. Revisiting Local PageRank Estimation on Undirected Graphs: Simple and Optimal.

    Hanzhi Wang

  73. Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization.

    Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou

  74. Unsupervised Heterogeneous Graph Rewriting Attack via Node Clustering.

    Haosen Wang, Can Xu, Chenglong Shi, Pengfei Zheng, Shiming Zhang, Minhao Cheng, Hongyang Chen

  75. Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs.

    Hewen Wang, Renchi Yang, Xiaokui Xiao

  76. A Novel Prompt Tuning for Graph Transformers: Tailoring Prompts to Graph Topologies.

    Jingchao Wang, Zhengnan Deng, Tongxu Lin, Wenyuan Li, Shaobin Ling

  77. The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field.

    Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Junfeng Fang, Xiaojiang Peng, Yuxuan Liang, Yang Wang

  78. The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs.

    Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang

  79. Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement.

    Yakun Wang, Daixin Wang, Hongrui Liu, Binbin Hu, Yingcui Yan, Qiyang Zhang, Zhiqiang Zhang

  80. AsyncET: Asynchronous Representation Learning for Knowledge Graph Entity Typing.

    Yun-Cheng Wang, Xiou Ge, Bin Wang, C.-C. Jay Kuo

  81. Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks.

    Yuwen Wang, Shunyu Liu, Tongya Zheng, Kaixuan Chen, Mingli Song

  82. Self-Supervised Learning for Graph Dataset Condensation.

    Yuxiang Wang, Xiao Yan, Shiyu Jin, Hao Huang, Quanqing Xu, Qingchen Zhang, Bo Du, Jiawei Jiang

  83. Dense Subgraph Discovery Meets Strong Triadic Closure.

    Chamalee Wickrama Arachchi, Iiro Kumpulainen, Nikolaj Tatti

  84. Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering.

    Yihong Wu, Le Zhang, Fengran Mo, Tianyu Zhu, Weizhi Ma, Jian-Yun Nie

  85. DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback.

    Yiqing Wu, Ruobing Xie, Zhao Zhang, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Yongjun Xu

  86. A Deep Prediction Framework for Multi-Source Information via Heterogeneous GNN.

    Zhen Wu, Jingya Zhou, Jinghui Zhang, Ling Liu, Chizhou Huang

  87. Fast Computation of Kemeny's Constant for Directed Graphs.

    Haisong Xia, Zhongzhi Zhang

  88. Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-level Anomaly Detection.

    Chunjing Xiao, Shikang Pang, Wenxin Tai, Yanlong Huang, Goce Trajcevski, Fan Zhou

  89. How to Avoid Jumping to Conclusions: Measuring the Robustness of Outstanding Facts in Knowledge Graphs.

    Hanhua Xiao, Yuchen Li, Yanhao Wang, Panagiotis Karras, Kyriakos Mouratidis, Natalia Rozalia Avlona

  90. Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification.

    Beini Xie, Heng Chang, Ziwei Zhang, Zeyang Zhang, Simin Wu, Xin Wang, Yuan Meng, Wenwu Zhu

  91. An Efficient Subgraph GNN with Provable Substructure Counting Power.

    Zuoyu Yan, Junru Zhou, Liangcai Gao, Zhi Tang, Muhan Zhang

  92. Balanced Confidence Calibration for Graph Neural Networks.

    Hao Yang, Min Wang, Qi Wang, Mingrui Lao, Yun Zhou

  93. Effective Clustering on Large Attributed Bipartite Graphs.

    Renchi Yang, Yidu Wu, Xiaoyang Lin, Qichen Wang, Tsz Nam Chan, Jieming Shi

  94. Graph Bottlenecked Social Recommendation.

    Yonghui Yang, Le Wu, Zihan Wang, Zhuangzhuang He, Richang Hong, Meng Wang

  95. Efficient and Effective Anchored Densest Subgraph Search: A Convex-programming based Approach.

    Xiaowei Ye, Rong-Hua Li, Lei Liang, Zhizhen Liu, Longlong Lin, Guoren Wang

  96. Embedding Two-View Knowledge Graphs with Class Inheritance and Structural Similarity.

    Kyuhwan Yeom, Hyeongjun Yang, Gayeon Park, Myeongheon Jeon, Yunjeong Ko, Byungkook Oh, Kyong-Ho Lee

  97. Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning.

    Wangyang Ying, Dongjie Wang, Xuanming Hu, Yuanchun Zhou, Charu C. Aggarwal, Yanjie Fu

  98. PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph.

    Dazhou Yu, Yuntong Hu, Yun Li, Liang Zhao

  99. Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data.

    Hanyang Yuan, Jiarong Xu, Cong Wang, Ziqi Yang, Chunping Wang, Keting Yin, Yang Yang

  100. Graph Cross Supervised Learning via Generalized Knowledge.

    Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang

  101. GPFedRec: Graph-Guided Personalization for Federated Recommendation.

    Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang

  102. Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction.

    Juzheng Zhang, Lanning Wei, Zhen Xu, Quanming Yao

  103. Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion.

    Qinggang Zhang, Keyu Duan, Junnan Dong, Pai Zheng, Xiao Huang

  104. Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling.

    Siwei Zhang, Xi Chen, Yun Xiong, Xixi Wu, Yao Zhang, Yongrui Fu, Yinglong Zhao, Jiawei Zhang

  105. Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks.

    Weijia Zhang, Le Zhang, Jindong Han, Hao Liu, Yanjie Fu, Jingbo Zhou, Yu Mei, Hui Xiong

  106. LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Yijian Qin, Wenwu Zhu

  107. Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective.

    Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang

  108. All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining.

    Haihong Zhao, Aochuan Chen, Xiangguo Sun, Hong Cheng, Jia Li

  109. Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs.

    Huanjing Zhao, Beining Yang, Yukuo Cen, Junyu Ren, Chenhui Zhang, Yuxiao Dong, Evgeny Kharlamov, Shu Zhao, Jie Tang

  110. Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling.

    Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang

  111. Conformalized Link Prediction on Graph Neural Networks.

    Tianyi Zhao, Jian Kang, Lu Cheng

  112. Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Broad Physical Dynamics Learning.

    Zinan Zheng, Yang Liu, Jia Li, Jianhua Yao, Yu Rong

  113. Bridging and Compressing Feature and Semantic Spaces for Robust Graph Neural Networks: An Information Theory Perspective.

    Luying Zhong, Renjie Lin, Jiayin Li, Shiping Wang, Zheyi Chen

  114. Efficient and Effective Implicit Dynamic Graph Neural Network.

    Yongjian Zhong, Hieu Vu, Tianbao Yang, Bijaya Adhikari

  115. Propagation Structure-Aware Graph Transformer for Robust and Interpretable Fake News Detection.

    Junyou Zhu, Chao Gao, Ze Yin, Xianghua Li, Jürgen Kurths

  116. One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes.

    Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen

  117. Topology-monitorable Contrastive Learning on Dynamic Graphs.

    Zulun Zhu, Kai Wang, Haoyu Liu, Jintang Li, Siqiang Luo

  118. Repeat-Aware Neighbor Sampling for Dynamic Graph Learning.

    Tao Zou, Yuhao Mao, Junchen Ye, Bowen Du

  119. Scalable Graph Learning for your Enterprise.

    Hema Raghavan

  120. LiGNN: Graph Neural Networks at LinkedIn.

    Fedor Borisyuk, Shihai He, Yunbo Ouyang, Morteza Ramezani, Peng Du, Xiaochen Hou, Chengming Jiang, Nitin Pasumarthy, Priya Bannur, Birjodh Tiwana, Ping Liu, Siddharth Dangi, Daqi Sun, Zhoutao Pei, Xiao Shi, Sirou Zhu, Qianqi Shen, Kuang-Hsuan Lee, David Stein, Baolei Li, Haichao Wei, Amol Ghoting, Souvik Ghosh

  121. CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification.

    Lele Cao, Vilhelm von Ehrenheim, Mark Granroth-Wilding, Richard Anselmo Stahl, Andrew McCornack, Armin Catovic, Dhiana Deva Cavalcanti Rocha

  122. CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning.

    Ulrik Friis-Jensen, Frederik L. Johansen, Andy S. Anker, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan

  123. Paths2Pair: Meta-path Based Link Prediction in Billion-Scale Commercial Heterogeneous Graphs.

    Jinquan Hang, Zhiqing Hong, Xinyue Feng, Guang Wang, Guang Yang, Feng Li, Xining Song, Desheng Zhang

  124. SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning.

    Kaidi Li, Tianmeng Yang, Min Zhou, Jiahao Meng, Shendi Wang, Yihui Wu, Boshuai Tan, Hu Song, Lujia Pan, Fan Yu, Zhenli Sheng, Yunhai Tong

  125. Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments.

    Yile Liang, Jiuxia Zhao, Donghui Li, Jie Feng, Chen Zhang, Xuetao Ding, Jinghua Hao, Renqing He

  126. DAG: Deep Adaptive and Generative K-Free Community Detection on Attributed Graphs.

    Chang Liu, Yuwen Yang, Yue Ding, Hongtao Lu, Wenqing Lin, Ziming Wu, Wendong Bi

  127. Integrating System State into Spatio Temporal Graph Neural Network for Microservice Workload Prediction.

    Yang Luo, Mohan Gao, Zhemeng Yu, Haoyuan Ge, Xiaofeng Gao, Tengwei Cai, Guihai Chen

  128. Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark.

    Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma

  129. MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning.

    Yu Sun, Kai Wang, Zhipeng Hu, Runze Wu, Yaoxin Wu, Wen Song, Xudong Shen, Tangjie Lv, Changjie Fan

  130. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction.

    Linghua Yang, Wantong Chen, Xiaoxi He, Shuyue Wei, Yi Xu, Zimu Zhou, Yongxin Tong

  131. OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining.

    Fanjin Zhang, Shijie Shi, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, Xiaoyan Li, Yuxiao Dong, Jie Tang

  132. Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks.

    Yijie Zhang, Yuanchen Bei, Hao Chen, Qijie Shen, Zheng Yuan, Huan Gong, Senzhang Wang, Feiran Huang, Xiao Huang

  133. GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection.

    Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan

  134. GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications.

    Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis

  135. Graph Reasoning with LLMs (GReaL).

    Anton Tsitsulin, Bryan Perozzi, Bahare Fatemi, Jonathan J. Halcrow

  136. Advances in Human Event Modeling: From Graph Neural Networks to Language Models.

    Songgaojun Deng, Maarten de Rijke, Yue Ning

  137. Graph Machine Learning Meets Multi-Table Relational Data.

    Quan Gan, Minjie Wang, David Wipf, Christos Faloutsos

  138. A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide.

    Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin

  139. Graph Intelligence with Large Language Models and Prompt Learning.

    Jia Li, Xiangguo Sun, Yuhan Li, Zhixun Li, Hong Cheng, Jeffrey Xu Yu

  140. A Review of Graph Neural Networks in Epidemic Modeling.

    Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin

  141. A Survey of Large Language Models for Graphs.

    Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh V. Chawla, Chao Huang

  142. Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods.

    Da Yan, Lyuheng Yuan, Akhlaque Ahmad, Chenguang Zheng, Hongzhi Chen, James Cheng

SIGIR-2024

  1. Transformer-based Reasoning for Learning Evolutionary Chain of Events on Temporal Knowledge Graph.

    Zhiyu Fang, Shuai-Long Lei, Xiaobin Zhu, Chun Yang, Shi-Xue Zhang, Xu-Cheng Yin, Jingyan Qin

  2. NativE: Multi-modal Knowledge Graph Completion in the Wild.

    Yichi Zhang, Zhuo Chen, Lingbing Guo, Yajing Xu, Binbin Hu, Ziqi Liu, Wen Zhang, Huajun Chen

  3. Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph Completion.

    Yu Zhao, Ying Zhang, Baohang Zhou, Xinying Qian, Kehui Song, Xiangrui Cai

  4. EditKG: Editing Knowledge Graph for Recommendation.

    Gu Tang, Xiaoying Gan, Jinghe Wang, Bin Lu, Lyuwen Wu, Luoyi Fu, Chenghu Zhou

  5. Amazon-KG: A Knowledge Graph Enhanced Cross-Domain Recommendation Dataset.

    Yuhan Wang, Qing Xie, Mengzi Tang, Lin Li, Jingling Yuan, Yongjian Liu

  6. Fair Sequential Recommendation without User Demographics.

    Huimin Zeng, Zhankui He, Zhenrui Yue, Julian J. McAuley, Dong Wang

  7. GraphGPT: Graph Instruction Tuning for Large Language Models.

    Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, Chao Huang

  8. Instruction-based Hypergraph Pretraining.

    Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

  9. LLM-enhanced Cascaded Multi-level Learning on Temporal Heterogeneous Graphs.

    Fengyi Wang, Guanghui Zhu, Chunfeng Yuan, Yihua Huang

  10. Hypergraph Convolutional Network for User-Oriented Fairness in Recommender Systems.

    Zhongxuan Han, Chaochao Chen, Xiaolin Zheng, Li Zhang, Yuyuan Li

  11. DHMAE: A Disentangled Hypergraph Masked Autoencoder for Group Recommendation.

    Yingqi Zhao, Haiwei Zhang, Qijie Bai, Changli Nie, Xiaojie Yuan

  12. AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations.

    Wei Wu, Chao Wang, Dazhong Shen, Chuan Qin, Liyi Chen, Hui Xiong

  13. Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative Filtering.

    Yi Zhang, Lei Sang, Yiwen Zhang

  14. Content-based Graph Reconstruction for Cold-start Item Recommendation.

    Jinri Kim, Eungi Kim, Kwangeun Yeo, Yujin Jeon, Chanwoo Kim, Sewon Lee, Joonseok Lee

  15. SIGformer: Sign-aware Graph Transformer for Recommendation.

    Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang, Shen Han, Chanfei Su, Yuqing Yuan, Can Wang

  16. TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems.

    Peiyan Zhang, Yuchen Yan, Xi Zhang, Chaozhuo Li, Senzhang Wang, Feiran Huang, Sunghun Kim

  17. Lightweight Embeddings for Graph Collaborative Filtering.

    Xurong Liang, Tong Chen, Lizhen Cui, Yang Wang, Meng Wang, Hongzhi Yin

  18. Graph Signal Diffusion Model for Collaborative Filtering.

    Yunqin Zhu, Chao Wang, Qi Zhang, Hui Xiong

  19. Disentangled Contrastive Hypergraph Learning for Next POI Recommendation.

    Yantong Lai, Yijun Su, Lingwei Wei, Tianqi He, Haitao Wang, Gaode Chen, Daren Zha, Qiang Liu, Xingxing Wang

  20. SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation.

    Yuxi Liu, Lianghao Xia, Chao Huang

  21. Grand: A Fast and Accurate Graph Retrieval Framework via Knowledge Distillation.

    Lin Lan, Pinghui Wang, Rui Shi, Tingqing Liu, Juxiang Zeng, Feiyang Sun, Yang Ren, Jing Tao, Xiaohong Guan

  22. Intent Distribution based Bipartite Graph Representation Learning.

    Haojie Li, Wei Wei, Guanfeng Liu, Jinhuan Liu, Feng Jiang, Junwei Du

  23. TGOnline: Enhancing Temporal Graph Learning with Adaptive Online Meta-Learning.

    Ruijie Wang, Jingyuan Huang, Yutong Zhang, Jinyang Li, Yufeng Wang, Wanyu Zhao, Shengzhong Liu, Charith Mendis, Tarek F. Abdelzaher

  24. Scalable Community Search over Large-scale Graphs based on Graph Transformer.

    Yuxiang Wang, Xiaoxuan Gou, Xiaoliang Xu, Yuxia Geng, Xiangyu Ke, Tianxing Wu, Zhiyuan Yu, Runhuai Chen, Xiangying Wu

  25. Untargeted Adversarial Attack on Knowledge Graph Embeddings.

    Tianzhe Zhao, Jiaoyan Chen, Yanchi Ru, Qika Lin, Yuxia Geng, Jun Liu

  26. GPT4Rec: Graph Prompt Tuning for Streaming Recommendation.

    Peiyan Zhang, Yuchen Yan, Xi Zhang, Liying Kang, Chaozhuo Li, Feiran Huang, Senzhang Wang, Sunghun Kim

  27. Let Me Show You Step by Step: An Interpretable Graph Routing Network for Knowledge-based Visual Question Answering.

    Duokang Wang, Linmei Hu, Rui Hao, Yingxia Shao, Xin Lv, Liqiang Nie, Juanzi Li

  28. CaseLink: Inductive Graph Learning for Legal Case Retrieval.

    Yanran Tang, Ruihong Qiu, Hongzhi Yin, Xue Li, Zi Huang

  29. A Persona-Infused Cross-Task Graph Network for Multimodal Emotion Recognition with Emotion Shift Detection in Conversations.

    Geng Tu, Feng Xiong, Bin Liang, Ruifeng Xu

  30. Graph Diffusive Self-Supervised Learning for Social Recommendation.

    Jiuqiang Li, Hongjun Wang

  31. Graph Reasoning Enhanced Language Models for Text-to-SQL.

    Zheng Gong, Ying Sun

  32. IdmGAE: Importance-Inspired Dynamic Masking for Graph Autoencoders.

    Ge Chen, Yulan Hu, Sheng Ouyang, Zhirui Yang, Yong Liu, Cuicui Luo

  33. Masked Graph Transformer for Large-Scale Recommendation.

    Huiyuan Chen, Zhe Xu, Chin-Chia Michael Yeh, Vivian Lai, Yan Zheng, Minghua Xu, Hanghang Tong

  34. Multi-view Mixed Attention for Contrastive Learning on Hypergraphs.

    Jongsoo Lee, Dong-Kyu Chae

  35. Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning.

    Zixu Wang, Bingbing Xu, Yige Yuan, Huawei Shen, Xueqi Cheng

  36. SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval.

    Zihao Li, Yuyi Ao, Jingrui He

  37. TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning.

    Jing Zhu, Xiang Song, Vassilis N. Ioannidis, Danai Koutra, Christos Faloutsos

  38. Turbo-CF: Matrix Decomposition-Free Graph Filtering for Fast Recommendation.

    Jin-Duk Park, Yong-Min Shin, Won-Yong Shin

  39. Unifying Graph Retrieval and Prompt Tuning for Graph-Grounded Text Classification.

    Le Dai, Yu Yin, Enhong Chen, Hui Xiong

  40. A Question-Answering Assistant over Personal Knowledge Graph.

    Lingyuan Liu, Huifang Du, Xiaolian Zhang, Mengying Guo, Haofen Wang, Meng Wang

  41. JPEC: A Novel Graph Neural Network for Competitor Retrieval in Financial Knowledge Graphs.

    Wanying Ding, Manoj Cherukumalli, Santosh Chikoti, Vinay K. Chaudhri

  42. unKR: A Python Library for Uncertain Knowledge Graph Reasoning by Representation Learning.

    Jingting Wang, Tianxing Wu, Shilin Chen, Yunchang Liu, Shutong Zhu, Wei Li, Jingyi Xu, Guilin Qi

  43. Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering.

    Zhentao Xu, Mark Jerome Cruz, Matthew Guevara, Tie Wang, Manasi Deshpande, Xiaofeng Wang, Zheng Li

  44. Graph-Based Audience Expansion Model for Marketing Campaigns.

    Md. Mostafizur Rahman, Daisuke Kikuta, Yu Hirate, Toyotaro Suzumura

NeurIPS-2024

  1. GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning

    Yanbin Wei, Shuai Fu, Weisen Jiang, Zejian Zhang, Zhixiong Zeng, Qi Wu, James T. Kwok, Yu Zhang

  2. Enhancing Chess Reinforcement Learning with Graph Representation

    Tomas Rigaux, Hisashi Kashima

  3. SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision

    Kseniya Cherenkova, Elona Dupont, Anis Kacem, Gleb Gusev, Djamila Aouada

  4. MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs

    Quentin Leboutet, Nina Wiedemann, zhipeng cai, Michael Paulitsch, Kai Yuan

  5. An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval

    Huilong Jin, Yingxue Zhang, Lei Shi, Shuang Zhang, Feifei Kou, Jiapeng Yang, Chuangying Zhu, Jia Luo

  6. Hamba: Single-view 3D Hand Reconstruction with Graph-guided Bi-Scanning Mamba

    Haoye Dong, Aviral Chharia, Wenbo Gou, Francisco Vicente Carrasco, Fernando D De la Torre

  7. Faster Local Solvers for Graph Diffusion Equations

    Jiahe Bai, Baojian Zhou, Deqing Yang, Yanghua Xiao

  8. DiGRAF: Diffeomorphic Graph-Adaptive Activation Function

    Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof

  9. FUG: Feature-Universal Graph Contrastive Pre-training for Graphs with Diverse Node Features

    Jitao Zhao, Di Jin, Meng Ge, Lianze Shan, Xin Wang, Dongxiao He, Zhiyong Feng

  10. Revisiting Score Propagation in Graph Out-of-Distribution Detection

    Longfei Ma, Yiyou Sun, Kaize Ding, Zemin Liu, Fei Wu

  11. On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models

    Boyao Li, Alexander Thomson, houssam nassif, Matthew Engelhard, David Page

  12. Generative Semi-supervised Graph Anomaly Detection

    Hezhe Qiao, Qingsong Wen, Xiaoli Li, Ee-peng Lim, Guansong Pang

  13. SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation

    Hang Yin, Xiuwei Xu, Zhenyu Wu, Jie Zhou, Jiwen Lu

  14. Can Graph Learning Improve Planning in LLM-based Agents?

    Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li

  15. Graph Neural Networks and Arithmetic Circuits

    Timon Barlag, Vivian Holzapfel, Laura Strieker, Jonni Virtema, Heribert Vollmer

  16. Schur Nets: exploiting local structure for equivariance in higher order graph neural networks

    QINGQI ZHANG, Ruize Xu, Risi Kondor

  17. Continuous Partitioning for Graph-Based Semi-Supervised Learning

    Chester Holtz, Pengwen Chen, Zhengchao Wan, Chung-Kuan Cheng, Gal Mishne

  18. LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings

    Duo Wang, Yuan Zuo, Fengzhi Li, Junjie Wu

  19. KnowGPT: Knowledge Graph based Prompting for Large Language Models

    Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang

  20. Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors

    VIET HO TAM THUC DO, Parham Eftekhar, Seyed Alireza Hosseini, Gene Cheung, Philip A. Chou

  21. A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning

    Yuanning Cui, Zequn Sun, Wei Hu

  22. Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation

    Lingxiao Zhao, Xueying Ding, Leman Akoglu

  23. Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

    Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang

  24. Graph Diffusion Transformers for Multi-Conditional Molecular Generation

    Gang Liu, Jiaxin Xu, Tengfei Luo, Meng Jiang

  25. Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks

    Arjun Subramonian, Jian Kang, Yizhou Sun

  26. Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning

    Jiapu Wang, Sun Kai, LINHAO LUO, Wei Wei, Yongli Hu, Alan Wee-Chung Liew, Shirui Pan, Baocai Yin

  27. Sample Efficient Bayesian Learning of Causal Graphs from Interventions

    Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu

  28. GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts

    Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Y Zou, Jure Leskovec

  29. Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding

    KE LIANG, Yue Liu, Hao Li, Lingyuan Meng, Suyuan Liu, Siwei Wang, sihang zhou, Xinwang Liu

  30. Graph Diffusion Policy Optimization

    Yijing Liu, Chao Du, Tianyu Pang, Chongxuan LI, Min Lin, Wei Chen

  31. UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training

    Biao Gong, Shuai Tan, Yutong Feng, Xiaoying Xie, Yuyuan Li, Chaochao Chen, Kecheng Zheng, Yujun Shen, Deli Zhao

  32. Deep Graph Mating

    Yongcheng Jing, Seok-Hee Hong, Dacheng Tao

  33. Spectral Graph Pruning Against Over-Squashing and Over-Smoothing

    Adarsh Jamadandi, Celia Rubio-Madrigal, Rebekka Burkholz

  34. What do Graph Neural Networks learn? Insights from Tropical Geometry

    Tuan Anh Pham, Vikas Garg

  35. Variational Flow Matching for Graph Generation

    Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent

  36. Road Network Representation Learning with the Third Law of Geography

    Haicang Zhou, Weiming Huang, Yile Chen, Tiantian He, Gao Cong, Yew Soon Ong

  37. Differentially Private Graph Diffusion with Applications in Personalized PageRanks

    Rongzhe Wei, Eli Chien, Pan Li

  38. IF-Font: Ideographic Description Sequence-Following Font Generation

    Xinping Chen, Xiao Ke, Wenzhong Guo

  39. G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training

    Che Liu, Cheng Ouyang, Sibo Cheng, Anand Shah, Wenjia Bai, Rossella Arcucci

  40. Mixture of Link Predictors on Graphs

    Li Ma, Haoyu Han, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang

  41. Cryptographic Hardness of Score Estimation

    Min Jae Song

  42. Linear Uncertainty Quantification of Graphical Model Inference

    Chenghua Guo, Han Yu, Jiaxin Liu, Chao Chen, Qi Li, Sihong Xie, Xi Zhang

  43. Supra-Laplacian Encoding for Transformer on Dynamic Graphs

    Yannis Karmim, Marc Lafon, Raphael Fournier-S'niehotta, Nicolas THOME

  44. The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks

    Christopher Blöcker, Chester Tan, Ingo Scholtes

  45. Multiview Scene Graph

    Juexiao Zhang, Gao Zhu, Sihang Li, Xinhao Liu, Haorui Song, Xinran Tang, Chen Feng

  46. Fairness-Aware Estimation of Graphical Models

    Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Qi Long, Li Shen

  47. Boosting Graph Pooling with Persistent Homology

    Chaolong Ying, Xinjian Zhao, Tianshu Yu

  48. FUGAL: Feature-fortified Unrestricted Graph Alignment

    Aditya Bommakanti, Harshith Vonteri, Konstantinos Skitsas, Sayan Ranu, Davide Mottin, Panagiotis Karras

  49. Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference

    Yonghan Jung, Min Woo Park, Sanghack Lee

  50. On the Scalability of GNNs for Molecular Graphs

    Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

  51. Efficient Streaming Algorithms for Graphlet Sampling

    Yann Bourreau, Marco Bressan, T-H. Hubert Chan, Qipeng Kuang, Mauro Sozio

  52. Linear Causal Bandits: Unknown Graph and Soft Interventions

    Zirui Yan, Ali Tajer

  53. Long-range Brain Graph Transformer

    Shuo Yu, Shan Jin, Ming Li, Tabinda Sarwar, Feng Xia

  54. What Matters in Graph Class Incremental Learning? An Information Preservation Perspective

    Jialu Li, Yu Wang, Pengfei Zhu, Wanyu Lin, Qinghua Hu

  55. Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?

    Jiacheng Cen, Anyi Li, Ning Lin, Yuxiang Ren, Zihe Wang, Wenbing Huang

  56. 4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs

    Minjie Wang, Quan Gan, David P. Wipf, Zheng Zhang, Christos Faloutsos, Weinan Zhang, Muhan Zhang, Zhenkun Cai, Jiahang Li, Zunyao Mao, Yakun Song, Jianheng Tang, Yanlin Zhang, Guang Yang, Chuan Lei, Xiao Qin, Ning Li, Han Zhang, Yanbo Wang, Zizhao Zhang

  57. Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction

    Haoran Luo, Haihong E, Yuhao Yang, Tianyu Yao, Yikai Guo, Zichen Tang, Wentai Zhang, Shiyao Peng, Kaiyang Wan, Meina Song, Wei Lin, Yifan Zhu, Anh Tuan Luu

  58. Probabilistic Graph Rewiring via Virtual Nodes

    Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert

  59. Multi-Chain Graphs of Graphs: A New Approach to Analyzing Blockchain Datasets

    Bingqiao Luo, Zhen Zhang, Qian Wang, Bingsheng He

  60. SubgDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning

    JIYING ZHANG, Zijing Liu, Yu Wang, Bin Feng, Yu Li

  61. Mind the Graph When Balancing Data for Fairness or Robustness

    Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa

  62. RAGraph: A General Retrieval-Augmented Graph Learning Framework

    Xinke Jiang, Rihong Qiu, Yongxin Xu, WentaoZhang, Yichen Zhu, Ruizhe Zhang, Yuchen Fang, Chu Xu, Junfeng Zhao, Yasha Wang

  63. Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs

    Franziska Heeg, Ingo Scholtes

  64. Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning

    Zhixiang Shen, Shuo Wang, Zhao Kang

  65. Active learning of neural population dynamics using two-photon holographic optogenetics

    Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew Bull, Karel Svoboda, Kayvon Daie, Matthew Golub, Kevin G. Jamieson

  66. Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning

    Yuefei Lyu, Chaozhuo Li, Sihong Xie, Xi Zhang

  67. Non-convolutional graph neural networks.

    Yuanqing Wang, Kyunghyun Cho

  68. Graph-based Uncertainty Metrics for Long-form Language Model Generations

    Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori B Hashimoto

  69. Bridge the Points: Graph-based Few-shot Segment Anything Semantically

    Anqi Zhang, Guangyu Gao, Jianbo Jiao, Chi Liu, Yunchao Wei

  70. Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting

    Zongjiang Shang, Ling Chen, Binqing Wu, Dongliang Cui

  71. Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention

    Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin

  72. Spiking Graph Neural Network on Riemannian Manifolds

    Li Sun, Zhenhao Huang, Qiqi Wan, Hao Peng, Philip S Yu

  73. Energy-based Epistemic Uncertainty for Graph Neural Networks

    Dominik Fuchsgruber, Tom Wollschläger, Stephan Günnemann

  74. FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference

    Zihan Tan, Guancheng Wan, Wenke Huang, Mang Ye

  75. Bridging OOD Detection and Generalization: A Graph-Theoretic View

    Han Wang, Sharon Li

  76. Unified Graph Augmentations for Generalized Contrastive Learning on Graphs

    Jiaming Zhuo, Yintong Lu, Hui Ning, Kun Fu, bingxin niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang

  77. Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs

    Liyi Chen, Panrong Tong, Zhongming Jin, Ying Sun, Jieping Ye, Hui Xiong

  78. GC-Bench: An Open and Unified Benchmark for Graph Condensation

    Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S Yu

  79. NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise

    Zhonghao Wang, Danyu Sun, Sheng Zhou, Haobo Wang, Jiapei Fan, Longtao Huang, Jiajun Bu

  80. Bayesian Optimization of Functions over Node Subsets in Graphs

    Huidong Liang, Xingchen Wan, Xiaowen Dong

  81. On the Power of Small-size Graph Neural Networks for Linear Programming

    Qian Li, Tian Ding, Linxin Yang, Minghui Ouyang, Qingjiang Shi, Ruoyu Sun

  82. HGDL: Heterogeneous Graph Label Distribution Learning

    Yufei Jin, Heng Lian, Yi He, Xingquan Zhu

  83. Graphcode: Learning from multiparameter persistent homology using graph neural networks

    Florian Russold, Michael Kerber

  84. Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks

    Joel Oskarsson, Tomas Landelius, Marc Deisenroth, Fredrik Lindsten

  85. Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation

    Xinhao Zheng, Yang Li, Cunxin Fan, Huaijin Wu, Xinhao Song, Junchi Yan

  86. GLBench: A Comprehensive Benchmark for Graph with Large Language Models

    Yuhan Li, Peisong Wang, Xiao Zhu, Aochuan Chen, Haiyun Jiang, Deng Cai, Wai Kin (Victor) Chan, Jia Li

  87. Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective

    YUJIE MO, Zhihe Lu, Runpeng Yu, Xiaofeng Zhu, Xinchao Wang

  88. Long-range Meta-path Search on Large-scale Heterogeneous Graphs

    Chao Li, Zijie Guo, qiuting he, Kun He

  89. R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction

    Ruyi Zha, Tao Jun Lin, Yuanhao Cai, Jiwen Cao, Yanhao Zhang, Hongdong Li

  90. A Motion-aware Spatio-temporal Graph for Video Salient Object Ranking

    Hao Chen, Zhu Yufei, Yongjian Deng

  91. GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction

    Shijin Duan, Ruyi Ding, Jiaxing He, Aidong Ding, Yunsi Fei, Xiaolin Xu

  92. Graph Neural Networks Do Not Always Oversmooth

    Bastian Epping, Alexandre René, Moritz Helias, Michael T Schaub

  93. Similarity-Navigated Conformal Prediction for Graph Neural Networks

    Jianqing Song, Jianguo Huang, Wenyu Jiang, Baoming Zhang, Shuangjie Li, Chongjun Wang

  94. FedGMark: Certifiably Robust Watermarking for Federated Graph Learning

    Yuxin Yang, Qiang Li, Yuan Hong, Binghui Wang

  95. Spatio-Spectral Graph Neural Networks

    Simon Markus Geisler, Arthur Kosmala, Daniel Herbst, Stephan Günnemann

  96. Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level

    Runlin Lei, Yuwei Hu, Yuchen Ren, Zhewei Wei

  97. TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering

    Jun Dan, Weiming Liu, Xie, Hua Yu, Shunjie Dong, Yanchao Tan

  98. GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning

    Guibin Zhang, Haonan Dong, yuchen zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang

  99. EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography

    Jehan Yang, Maxwell Soh, Vivianna Lieu, Douglas Weber, Zackory Erickson

  100. Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images

    Shengjun Zhang, Xin Fei, Fangfu Liu, Haixu Song, Yueqi Duan

  101. ARC: A Generalist Graph Anomaly Detector with In-Context Learning

    Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan

  102. Graph Convolutions Enrich the Self-Attention in Transformers!

    Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park

  103. Unelicitable Backdoors via Cryptographic Transformer Circuits

    Andis Draguns, Andrew Gritsevskiy, Sumeet Motwani, Christian Schroeder de Witt

  104. Idiographic Personality Gaussian Process for Psychological Assessment

    Yehu Chen, Muchen Xi, Joshua Jackson, Jacob Montgomery, Roman Garnett

  105. DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach

    Qian Chen, Ling Chen

  106. Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism

    Ronast Subedi, Lu Wei, Wenhan Gao, Shayok Chakraborty, Yi Liu

  107. emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation

    Sasha Salter, Richard Warren, Collin Schlager, Adrian Spurr, Shangchen Han, Rohin Bhasin, Yujun Cai, Peter Walkington, Anuoluwapo Bolarinwa, Robert J. Wang, Nathan Danielson, Josh S Merel, Eftychios A Pnevmatikakis, Jesse Marshall

  108. Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model

    Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Imran Razzak, Bram Hoex, Haofen Wang, Tong Xie, Wenjie Zhang

  109. Enhancing Graph Transformers with Hierarchical Distance Structural Encoding

    Yuankai Luo, Hongkang Li, Lei Shi, Xiao-Ming Wu

  110. Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series

    Giangiacomo Mercatali, Andre Freitas, Jie Chen

  111. Learning on Large Graphs using Intersecting Communities

    Ben Finkelshtein, Ismail Ceylan, Michael Bronstein, Ron Levie

  112. Challenges of Generating Structurally Diverse Graphs

    Fedor Velikonivtsev, Mikhail Mironov, Liudmila Prokhorenkova

  113. Robust Offline Active Learning on Graphs

    Yuanchen Wu, Yubai Yuan

  114. EGODE: An Event-attended Graph ODE Framework for Modeling Rigid Dynamics

    Jingyang Yuan, Gongbo Sun, Zhiping Xiao, Hang Zhou, Xiao Luo, Junyu Luo, Yusheng Zhao, Wei Ju, Ming Zhang

  115. DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment

    Gongpei Zhao, Tao Wang, Congyan Lang, Yi Jin, Yidong Li, Haibin Ling

  116. Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric Videos

    Luigi Seminara, Giovanni Maria Farinella, Antonino Furnari

  117. Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits

    Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel

  118. ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses

    Junjie Ni, Guofeng Zhang, Guanglin Li, Yijin Li, Xinyang Liu, Zhaoyang Huang, Hujun Bao

  119. TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs

    Zhuofeng Li, Zixing Gou, Xiangnan Zhang, Zhongyuan Liu, Sirui Li, Yuntong Hu, Chen LING, Zheng Zhang, Liang Zhao

  120. Unsupervised Homography Estimation on Multimodal Image Pair via Alternating Optimization

    Sanghyeob Song, Jaihyun Lew, Hyemi Jang, Sungroh Yoon

  121. Gradient Rewiring for Editable Graph Neural Network Training

    Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Hu

  122. Unifying Generation and Prediction on Graphs with Latent Graph Diffusion

    Cai Zhou, Xiyuan Wang, Muhan Zhang

  123. UGC: Universal Graph Coarsening

    Mohit Kataria, Sandeep Kumar, Jayadeva Dr

  124. Semi-Open 3D Object Retrieval via Hierarchical Equilibrium on Hypergraph

    Yang Xu, Yifan Feng, Jun Zhang, Jun-Hai Yong, Yue Gao

  125. Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images

    Junxian Wu, Xinyi Ke, XIAOMING JIANG, Huanwen Wu, Youyong Kong, Lizhi Shao

  126. Stochastic contextual bandits with graph feedback: from independence number to MAS number

    Yuxiao Wen, Yanjun Han, Zhengyuan Zhou

  127. Federated Graph Learning for Cross-Domain Recommendation

    Ziqi Yang, Zhaopeng Peng, Zihui Wang, Jianzhong Qi, Chaochao Chen, Weike Pan, Chenglu Wen, Cheng Wang, Xiaoliang Fan

  128. Microstructures and Accuracy of Graph Recall by Large Language Models

    Yanbang Wang, Hejie Cui, Jon M. Kleinberg

  129. On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks

    Jiong Zhu, Gaotang Li, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra

  130. Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover

    Tam Nguyen, Anh-Dzung Doan, zhipeng cai, Tat-Jun Chin

  131. Knowledge-Empowered Dynamic Graph Network for Irregularly Sampled Medical Time Series

    Yicheng Luo, Zhen Liu, Linghao Wang, Binquan Wu, Junhao Zheng, Qianli Ma

  132. GraphVis: Boosting LLMs with Visual Knowledge Graph Integration

    Yihe Deng, Chenchen Ye, Zijie Huang, Mingyu Derek Ma, Yiwen Kou, Wei Wang

  133. Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module

    Jingbo Zhou, Yixuan Du, Ruqiong Zhang, Jun Xia, Zhizhi Yu, Zelin Zang, Di Jin, Carl Yang, Rui Zhang, Stan Z. Li

  134. What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks

    Yilun Zheng, Sitao Luan, Lihui Chen

  135. GraphMorph: Tubular Structure Extraction by Morphing Predicted Graphs

    Zhao Zhang, Ziwei Zhao, Dong Wang, Liwei Wang

  136. Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach

    Hanyang Yuan, Jiarong Xu, Renhong Huang, Mingli Song, Chunping Wang, YANG YANG

  137. Improving Generalization of Dynamic Graph Learning via Environment Prompt

    Kuo Yang, Zhengyang Zhou, Qihe Huang, Limin Li, Yuxuan Liang, Yang Wang

  138. Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem

    Mathieu Even, Luca Ganassali, Jakob Maier, Laurent Massoulié

  139. Neural Cover Selection for Image Steganography

    Karl Chahine, Hyeji Kim

  140. Even Sparser Graph Transformers

    Hamed Shirzad, Honghao Lin, Balaji Venkatachalam, Ameya Velingker, David Woodruff, Danica J. Sutherland

  141. Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections

    Zihan Luo, Hong Huang, Yongkang Zhou, Jiping Zhang, Nuo Chen, Hai Jin

  142. Integrating GNN and Neural ODEs for Estimating Non-Reciprocal Two-Body Interactions in Mixed-Species Collective Motion

    Masahito Uwamichi, Simon Schnyder, Tetsuya J. Kobayashi, Satoshi Sawai

  143. Are Graph Neural Networks Optimal Approximation Algorithms?

    Morris Yau, Nikolaos Karalias, Eric Lu, Jessica Xu, Stefanie Jegelka

  144. Graph Edit Distance with General Costs Using Neural Set Divergence

    Eeshaan Jain, Indradyumna Roy, Saswat Meher, Soumen Chakrabarti, Abir De

  145. Secret Collusion among AI Agents: Multi-Agent Deception via Steganography

    Sumeet Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip Torr, Lewis Hammond, Christian Schroeder de Witt

  146. Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval

    Ashwin Ramachandran, Vaibhav Raj, Indradyumna Roy, Soumen Chakrabarti, Abir De

  147. Understanding Transformer Reasoning Capabilities via Graph Algorithms

    Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni

  148. RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks

    Jiaxing Zhang, Zhuomin Chen, hao mei, Longchao Da, Dongsheng Luo, Hua Wei

  149. Discrete-state Continuous-time Diffusion for Graph Generation

    Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong

  150. Graph Neural Networks Need Cluster-Normalize-Activate Modules

    Arseny Skryagin, Felix Divo, Mohammad Amin Ali, Devendra S Dhami, Kristian Kersting

  151. Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs

    Ma Rong, Jie Chen, Xiangyang Xue, Jian Pu

  152. Dissecting the Failure of Invariant Learning on Graphs

    Qixun Wang, Yifei Wang, Yisen Wang, Xianghua Ying

  153. Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution

    Cong Xu, Jun Wang, Jianyong Wang, Wei Zhang

  154. Towards Harmless Rawlsian Fairness Regardless of Demographic Prior

    Xuanqian Wang, Jing Li, Ivor W. Tsang, Yew Soon Ong

  155. Towards Dynamic Message Passing on Graphs

    Junshu Sun, Chenxue Yang, Xiangyang Ji, Qingming Huang, Shuhui Wang

  156. A Structure-Aware Framework for Learning Device Placements on Computation Graphs

    Shukai Duan, Heng Ping, Nikos Kanakaris, Xiongye Xiao, Panagiotis Kyriakis, Nesreen K. Ahmed, Peiyu Zhang, Guixiang Ma, Mihai Capotă, Shahin Nazarian, Theodore Willke, Paul Bogdan

  157. Generalizing CNNs to graphs with learnable neighborhood quantization

    Isaac Osafo Nkansah, Neil Gallagher, Ruchi Sandilya, Conor Liston, Logan Grosenick

  158. DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ

    Jonas Belouadi, Simone Ponzetto, Steffen Eger

  159. Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers

    Jinsong Chen, Hanpeng Liu, John Hopcroft, Kun He

  160. Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach

    Chaoxi Niu, Guansong Pang, Ling Chen, Bing Liu

  161. GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting

    Umangi Jain, Ashkan Mirzaei, Igor Gilitschenski

  162. Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation

    Meihan Liu, Zhen Zhang, Jiachen Tang, Jiajun Bu, Bingsheng He, Sheng Zhou

  163. DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction

    Bowen Song, Jason Hu, Zhaoxu Luo, Jeffrey Fessler, Liyue Shen

  164. DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation

    Hongyuan Tao, Hang Yu, Jianguo Li

  165. Continuous Product Graph Neural Networks

    Aref Einizade, Fragkiskos Malliaros, Jhony H. Giraldo

  166. CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos

    Trong-Thuan Nguyen, Pha Nguyen, Xin Li, Jackson Cothren, Alper Yilmaz, Khoa Luu

  167. GRANOLA: Adaptive Normalization for Graph Neural Networks

    Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron

  168. The Intelligible and Effective Graph Neural Additive Network

    Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

  169. Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust

    Hongjie Chen, Jingqiu Ding, Yiding Hua, David Steurer

  170. On provable privacy vulnerabilities of graph representations

    Ruofan Wu, Guanhua Fang, Mingyang Zhang, Qiying Pan, Tengfei LIU, Weiqiang Wang

  171. Graph Learning for Numeric Planning

    Dillon Chen, Sylvie Thiebaux

  172. emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography

    Viswanath Sivakumar, Jeffrey Seely, Alan Du, Sean Bittner, Adam Berenzweig, Anuoluwapo Bolarinwa, Alex Gramfort, Michael I. Mandel

  173. DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs

    Jiasheng Zhang, Jialin Chen, Menglin Yang, Aosong Feng, Shuang Liang, Jie Shao, Rex Ying

  174. DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis

    Shangshang Yang, Mingyang Chen, Ziwen Wang, Xiaoshan Yu, Panpan Zhang, Haiping Ma, Xingyi Zhang

  175. Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles

    Rui Duan, Mingjian Guang, Junli Wang, Chungang Yan, Hongda Qi, Wenkang Su, Can Tian, Haoran Yang

  176. Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks

    Mitchell Keren Taraday, Almog David, Chaim Baskin

  177. Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed

    Katherine Tieu, Dongqi Fu, Yada Zhu, Hendrik Hamann, Jingrui He

  178. ProG: A Graph Prompt Learning Benchmark

    Chenyi Zi, Haihong Zhao, Xiangguo Sun, Yiqing Lin, Hong Cheng, Jia Li

  179. Graph neural networks and non-commuting operators

    Mauricio Velasco, Kaiying O'Hare, Bernardo Rychtenberg, Soledad Villar

  180. Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy

    Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang, Kyungho Kim, Jaemin Yoo, Kijung Shin

  181. Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification

    Yuankai Luo, Lei Shi, Xiao-Ming Wu

  182. Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation

    Yunnan Wang, Ziqiang Li, Wenyao Zhang, Zequn Zhang, Baao Xie, Xihui Liu, Wenjun Zeng, Xin Jin

  183. Uncovering the Redundancy in Graph Self-supervised Learning Models

    Zhibiao Wang, Xiao Wang, Haoyue Deng, Nian Liu, Shirui Pan, Chunming Hu

  184. A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening

    Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron

  185. Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss

    Paul Krzakala, Junjie Yang, Rémi Flamary, Florence d'Alché-Buc, Charlotte Laclau, Matthieu Labeau

  186. CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search

    Ming Yang, Yuzheng Cai, Weiguo Zheng

  187. Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models

    Baao Xie, Qiuyu Chen, Yunnan Wang, Zequn Zhang, Xin Jin, Wenjun Zeng

  188. Distributed-Order Fractional Graph Operating Network

    Kai Zhao, Xuhao Li, Qiyu Kang, Feng Ji, Qinxu Ding, Yanan Zhao, Wenfei Liang, Wee Peng Tay

  189. Logical characterizations of recurrent graph neural networks with reals and floats

    Veeti Ahvonen, Damian Heiman, Antti Kuusisto, Carsten Lutz

  190. PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling

    Hao Wu, Changhu Wang, Fan Xu, Jinbao Xue, Chong Chen, Xian-Sheng Hua, Xiao Luo

  191. Visual Data Diagnosis and Debiasing with Concept Graphs

    Rwiddhi Chakraborty, Yinong O Wang, Jialu Gao, Runkai Zheng, Cheng Zhang, Fernando D De la Torre

  192. Scale Equivariant Graph Metanetworks

    Ioannis Kalogeropoulos, Giorgos Bouritsas, Yannis Panagakis

  193. GFT: Graph Foundation Model with Transferable Tree Vocabulary

    Zehong Wang, Zheyuan Zhang, Nitesh Chawla, Chuxu Zhang, Yanfang Ye

  194. Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond

    Kirill Brilliantov, Amauri Souza, Vikas Garg

  195. Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction

    Haotong Du, Quanming Yao, Juzheng Zhang, Yang Liu, Zhen Wang

  196. Robust Graph Neural Networks via Unbiased Aggregation

    Zhichao Hou, Ruiqi Feng, Tyler Derr, Xiaorui Liu

  197. Knowledge Graph Completion by Intermediate Variables Regularization

    Changyi Xiao, Yixin Cao

  198. PowerGraph: A power grid benchmark dataset for graph neural networks

    Anna Varbella, Kenza Amara, Blazhe Gjorgiev, Mennatallah El-Assady, Giovanni Sansavini

  199. Motion Graph Unleashed: A Novel Approach to Video Prediction

    Yiqi Zhong, Luming Liang, Bohan Tang, Ilya Zharkov, Ulrich Neumann

  200. Non-Euclidean Mixture Model for Social Network Embedding

    Roshni Iyer, Yewen Wang, Wei Wang, Yizhou Sun

  201. Graph Coarsening with Message-Passing Guarantees

    Antonin Joly, Nicolas Keriven

  202. Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering

    Dongxiao He, Lianze Shan, Jitao Zhao, Hengrui Zhang, Zhen Wang, Weixiong Zhang

  203. Efficient Graph Matching for Correlated Stochastic Block Models

    Shuwen Chai, Miklos Z. Racz

  204. Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network

    Xiao Guo, Vishal Asnani, Sijia Liu, Xiaoming Liu

  205. DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks

    ZEYU ZHANG, Lu Li, Shuyan Wan, Wang, Zhiyi Wang, Zhiyuan Lu, Dong Hao, Wanli Li

  206. InstructG2I: Synthesizing Images from Multimodal Attributed Graphs

    Bowen Jin, Ziqi Pang, Bingjun Guo, Yu-Xiong Wang, Jiaxuan You, Jiawei Han

  207. Regression under demographic parity constraints via unlabeled post-processing

    Gayane Taturyan, Evgenii Chzhen, Mohamed Hebiri

  208. On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks

    Paolo Pellizzoni, Till Hendrik Schulz, Dexiong Chen, Karsten Borgwardt

  209. Neural P$^3$M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs

    Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, Nanning Zheng

  210. EyeGraph: Modularity-aware Spatio Temporal Graph Clustering for Continuous Event-based Eye Tracking

    Nuwan Bandara, Thivya Kandappu, Argha Sen, Ila Gokarn, Archan Misra

  211. EGSST: Event-based Graph Spatiotemporal Sensitive Transformer for Object Detection

    Sheng Wu, Hang Sheng, Hui Feng, Bo Hu

  212. Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning

    Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok

  213. Accelerating Non-Maximum Suppression: A Graph Theory Perspective

    King-Siong Si, Lu Sun, Weizhan Zhang, Tieliang Gong, Jiahao Wang, Jiang Liu, Hao Sun

  214. UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction

    Yansong Ning, Hao Liu

  215. GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules

    Burouj Armgaan, Manthan Dalmia, Sourav Medya, Sayan Ranu

  216. Rethinking the Capacity of Graph Neural Networks for Branching Strategy

    Ziang Chen, Jialin Liu, Xiaohan Chen, Wang, Wotao Yin

  217. FairWire: Fair Graph Generation

    Oyku Kose, Yanning Shen

  218. Almost Surely Asymptotically Constant Graph Neural Networks

    Sam Adam-Day, Michael Benedikt, Ismail Ceylan, Ben Finkelshtein

  219. Assembly Fuzzy Representation on Hypergraph for Open-Set 3D Object Retrieval

    Yang Xu, Yifan Feng, Jun Zhang, Jun-Hai Yong, Yue Gao

  220. Dynamic Rescaling for Training GNNs

    Nimrah Mustafa, Rebekka Burkholz

  221. Towards Principled Graph Transformers

    Luis Müller, Daniel Kusuma, Blai Bonet, Christopher Morris

  222. State Space Models on Temporal Graphs: A First-Principles Study

    Jintang Li, Ruofan Wu, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng

  223. HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning

    Lu Bai, Zhuo Xu, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock

  224. Analysis of Corrected Graph Convolutions

    Robert J. Wang, Aseem Baranwal, Kimon Fountoulakis

  225. Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters

    Ya-Wei Eileen Lin, Ronen Talmon, Ron Levie

  226. DistrictNet: Decision-aware learning for geographical districting

    Cheikh Ahmed, Alexandre Forel, Axel Parmentier, Thibaut Vidal

  227. Graph Structure Inference with BAM: Neural Dependency Processing via Bilinear Attention

    Philipp Froehlich, Heinz Koeppl

  228. An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning

    Dong Li, Aijia Zhang, Junqi Gao, Biqing Qi

  229. PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation

    ChenRui Duan, Zelin Zang, Siyuan Li, Yongjie Xu, Stan Z. Li

  230. LLaMo: Large Language Model-based Molecular Graph Assistant

    Jinyoung Park, Minseong Bae, Dohwan Ko, Hyunwoo J Kim

  231. Scene Graph Generation with Role-Playing Large Language Models

    Guikun Chen, Jin Li, Wenguan Wang

  232. Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification

    Yihong Luo, Yuhan Chen, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang

  233. A Topology-aware Graph Coarsening Framework for Continual Graph Learning

    Xiaoxue Han, Zhuo Feng, Yue Ning

  234. G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

    Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi

  235. A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs

    Haoxuan Li, Yue Liu, Zhi Geng, Kun Zhang

  236. DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph

    Zhehao Zhang, Jiaao Chen, Diyi Yang

  237. UniGAD: Unifying Multi-level Graph Anomaly Detection

    Yiqing Lin, Jianheng Tang, Chenyi Zi, H. Vicky Zhao, Yuan Yao, Jia Li

  238. KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledge

    Pengcheng Jiang, Lang Cao, Cao (Danica) Xiao, Parminder Bhatia, Jimeng Sun, Jiawei Han

  239. Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks

    Xuyuan Liu, Yinghao Cai, Qihui Yang, Yujun Yan

  240. Adaptive Visual Scene Understanding: Incremental Scene Graph Generation

    Naitik Khandelwal, Xiao Liu, Mengmi Zhang

  241. Unitary Convolutions for Learning on Graphs and Groups

    Bobak Kiani, Lukas Fesser, Melanie Weber

  242. Generative Modelling of Structurally Constrained Graphs

    Manuel Madeira, Clement Vignac, Dorina Thanou, Pascal Frossard

  243. Graph Classification via Reference Distribution Learning: Theory and Practice

    Zixiao Wang, Jicong Fan

  244. Diffusion Twigs with Loop Guidance for Conditional Graph Generation

    Giangiacomo Mercatali, Yogesh Verma, Andre Freitas, Vikas Garg

  245. Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior

    Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra

  246. TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs

    Julia Gastinger, Shenyang Huang, Michael Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau

  247. MOTIVE: A Drug-Target Interaction Graph For Inductive Link Prediction

    John Arevalo, Ellen Su, Anne Carpenter, Shantanu Singh

  248. Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models

    Xin Li, Weize Chen, Qizhi Chu, Haopeng Li, Zhaojun Sun, Ran Li, Chen Qian, Yiwei Wei, Chuan Shi, Zhiyuan Liu, Maosong Sun, Cheng Yang

CIKM-2024

  1. Novelty-aware Graph Traversal and Expansion for Hierarchical Reinforcement Learning

    Jongchan Park,Seungjun Oh,Yusung Kim

  2. Mining Path Association Rules in Large Property Graphs

    Yuya Sasaki,Panagiotis Karras

  3. PSNE: Efficient Spectral Sparsification Algorithms for Scaling Network Embedding

    Longlong Lin,Yunfeng Yu,Zihao Wang,Zeli Wang,Yuying Zhao,Jin Zhao,Tao Jia

  4. A Geometric Perspective for High-Dimensional Multiplex Graphs

    Kamel Abdous,Nairouz Mrabah,Mohamed Bouguessa

  5. Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs

    Vardaan Pahuja,Weidi Luo,Yu Gu,Cheng-Hao Tu,Hong-You Chen,Tanya Berger-Wolf,Charles Stewart,Song Gao,Wei-Lun Chao,Yu Su

  6. Hierarchical Graph Latent Diffusion Model for Conditional Molecule Generation

    Tian Bian,Yifan Niu,Heng Chang,Divin Yan,Junzhou Huang,Yu Rong,Tingyang Xu,Jia Li,Hong Cheng

  7. ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance

    Ling-Hao Chen,Yuanshuo Zhang,Taohua Huang,Liangcai Su,Zeyi Lin,Xi Xiao,Xiaobo Xia,Tongliang Liu

  8. Prompt-Based Spatio-Temporal Graph Transfer Learning

    Junfeng Hu,Xu Liu,Zhencheng Fan,Yifang Yin,Shili Xiang,Savitha Ramasamy,Roger Zimmermann

  9. Hypergraph Hash Learning for Efficient Trajectory Similarity Computation

    Yuan Cao,Lei Li,Xiangru Chen,Xue Xu,Zuojin Huang,Yanwei Yu

  10. Veracity Estimation for Entity-Oriented Search with Knowledge Graphs

    Stefano Marchesin,Gianmaria Silvello,Omar Alonso

  11. Behavior-Aware Hypergraph Convolutional Network for Illegal Parking Prediction with Multi-Source Contextual Information

    Guang Yang,Meiqi Tu,Zelong Li,Jinquan Hang,Taichi Liu,Ruofeng Liu,Yi Ding,Yu Yang,Desheng Zhang

  12. DTFormer: A Transformer-Based Method for Discrete-Time Dynamic Graph Representation Learning

    Xi Chen,Yun Xiong,Siwei Zhang,Jiawei Zhang,Yao Zhang,Shiyang Zhou,Xixi Wu,Mingyang Zhang,Tengfei Liu,Weiqiang Wang

  13. iMIRACLE: An Iterative Multi-View Graph Neural Network to Model Intercellular Gene Regulation From Spatial Transcriptomic Data

    Ziheng Duan,Siwei Xu,Cheyu Lee,Dylan Riffle,Jing Zhang

  14. Graph Anomaly Detection with Adaptive Node Mixup

    Qinghai Zhou,Yuzhong Chen,Zhe Xu,Yuhang Wu,Menghai Pan,Mahashweta Das,Hao Yang,Hanghang Tong

  15. Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets

    Sabyasachi Basu,Daniel Paul-Pena,Kun Qian,C. Seshadhri,Edward W Huang,Karthik Subbian

  16. Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation

    Lirong Wu,Yunfan Liu,Haitao Lin,Yufei Huang,Stan Z. Li

  17. Language Models-enhanced Semantic Topology Representation Learning For Temporal Knowledge Graph Extrapolation

    Tianli Zhang,Tongya Zheng,Zhenbang Xiao,Zulong Chen,Liangyue Li,Zunlei Feng,Dongxiang Zhang,Mingli Song

  18. Shape-aware Graph Spectral Learning

    Junjie Xu,Enyan Dai,Dongsheng Luo,Xiang Zhang,Suhang Wang

  19. Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis

    Zhe Liu,Xiang Huang,Jingyun Zhang,Zhifeng Hao,Li Sun,Hao Peng

  20. GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation

    Guojiao Lin,Meng Zhen,Dongjie Wang,Qingqing Long,Yuanchun Zhou,Meng Xiao

  21. HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training

    Fali Wang,Tianxiang Zhao,Junjie Xu,Suhang Wang

  22. GraphCBAL: Class-Balanced Active Learning for Graph Neural Networks via Reinforcement Learning

    Chengcheng Yu,Jiapeng Zhu,Xiang Li

  23. MOAT: Graph Prompting for 3D Molecular Graphs

    Qingqing Long,Yuchen Yan,Wentao Cui,Wei Ju,Zhihong Zhu,Yuanchun Zhou,Xuezhi Wang,Meng Xiao

  24. A General Strategy Graph Collaborative Filtering for Recommendation Unlearning

    Yongjing Hao,Fuzhen Zhuang,Deqing Wang,Guanfeng Liu,Victor S. Sheng,Pengpeng Zhao

  25. Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation

    Baoyu Jing,Dawei Zhou,Kan Ren,Carl Yang

  26. Using Distributed Ledgers To Build Knowledge Graphs For Decentralized Computing Ecosystems

    Tarek Zaarour,Ahmed Khalid,Preeja Pradeep,Ahmed Zahran

  27. DDIPrompt: Drug-Drug Interaction Event Prediction based on Graph Prompt Learning

    Yingying Wang,Yun Xiong,Xixi Wu,Xiangguo Sun,Jiawei Zhang,GuangYong Zheng

  28. When LLM Meets Hypergraph: A Sociological Analysis on Personality via Online Social Networks

    Zhiyao Shu,Xiangguo Sun,Hong Cheng

  29. DPCAG: A Community Affiliation Graph Generation Model for Preserving Group Relationships

    Xinjian Zhang,Bo Ning,Chengfei Liu

  30. RD-P: A Trustworthy Retrieval-Augmented Prompter with Knowledge Graphs for LLMs

    Yubo Huang,Guosun Zeng

  31. Inductive Knowledge Graph Embedding via Exploring Interaction Patterns of Relations

    Chong Mu,Lizong Zhang,Jinchuan Zhang,Qian Huang,Zhiguo Wang

  32. Data Imputation from the Perspective of Graph Dirichlet Energy

    Weiqi Zhang,Guanlue Li,Jianheng Tang,Jia Li,Fugee Tsung

  33. DiHAN: A Novel Dynamic Hierarchical Graph Attention Network for Fake News Detection

    Ya-Ting Chang,Zhibo Hu,Xiaoyu Li,Shuiqiao Yang,Jiaojiao Jiang,Nan Sun

  34. SALA: Scenario-aware Label Graph Interaction for Multi-intent Spoken Language Understanding

    Zhihong Zhu,Xuxin Cheng,Zhanpeng Chen,Zhichang Wang,Zhiqi Huang,Yuexian Zou

  35. Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding

    Yichen Liu,Jiawei Chen,Defang Chen,Zhehui Zhou,Yan Feng,Can Wang

  36. Hyperedge Importance Estimation via Identity-aware Hypergraph Attention Network

    Yin Chen,Xiaoyang Wang,Chen Chen

  37. Debiased Graph Poisoning Attack via Contrastive Surrogate Objective

    Kanghoon Yoon,Yeonjun In,Namkyeong Lee,Kibum Kim,Chanyoung Park

  38. ByGCN: Spatial Temporal Byroad-Aware Graph Convolution Network for Traffic Flow Prediction in Road Networks

    Tangpeng Dan,Xiao Pan,Bolong Zheng,Xiaofeng Meng

  39. MoTTo: Scalable Motif Counting with Time-aware Topology Constraint for Large-scale Temporal Graphs

    Jiantao Li,Jianpeng Qi,Yueling Huang,Lei Cao,Yanwei Yu,Junyu Dong

  40. Bi-directional Learning of Logical Rules with Type Constraints for Knowledge Graph Completion

    Kunxun Qi,Jianfeng Du,Hai Wan

  41. FCS-HGNN: Flexible Multi-type Community Search in Heterogeneous Information Networks

    Guoxin Chen,Fangda Guo,Yongqing Wang,Yanghao Liu,Peiying Yu,Huawei Shen,Xueqi Cheng

  42. Integrating Structure and Text for Enhancing Hyper-relational Knowledge Graph Representation via Structure Soft Prompt Tuning

    Lijie Li,Hui Wang,Jiahang Li,Xiaodi Xu,Ye Wang,Tao Ren

  43. HGCH: A Hyperbolic Graph Convolution Network Model for Heterogeneous Collaborative Graph Recommendation

    Lu Zhang,Ning Wu

  44. Multi-Modal Sarcasm Detection via Graph Convolutional Network and Dynamic Network

    Jiaqi Hao,Junfeng Zhao,Zhigang Wang

  45. Spatio-temporal Graph Normalizing Flow for Probabilistic Traffic Prediction

    Yang An,Zhibin Li,Wei Liu,Haoliang Sun,Meng Chen,Wenpeng Lu,Yongshun Gong

  46. Effective Illicit Account Detection on Large Cryptocurrency MultiGraphs

    Zhihao Ding,Jieming Shi,Qing Li,Jiannong Cao

  47. A Mixed-Curvature Graph Diffusion Model

    Yujie Wang,Shuo Zhang,Junda Ye,Hao Peng,Li Sun

  48. MuLe: Multi-Grained Graph Learning for Multi-Behavior Recommendation

    Seunghan Lee,Geonwoo Ko,Hyun-Je Song,Jinhong Jung

  49. SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection

    Zhihao Ding,Jieming Shi,Shiqi Shen,Xuequn Shang,Jiannong Cao,Zhipeng Wang,Zhi Gong

  50. Towards Coarse-grained Visual Language Navigation Task Planning Enhanced by Event Knowledge Graph

    Kaichen Zhao,Yaoxian Song,Haiquan Zhao,Haoyu Liu,Tiefeng Li,Zhixu Li

  51. Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

    Yuanyuan Liang,Keren Tan,Tingyu Xie,Wenbiao Tao,Siyuan Wang,Yunshi Lan,Weining Qian

  52. PTSR: Prefix-Target Graph-based Sequential Recommendation

    Jiayu Chen,Xiaoyu Du,Yonghua Pan,Jinhui Tang

  53. Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion

    Zhuofeng Li,Haoxiang Zhang,Qiannan Zhang,Ziyi Kou,Shichao Pei

  54. SGES: A General and Space-efficient Framework for Graphlet Counting in Graph Streams

    Chen Yang,Lailong Luo,Yuliang Lu,Chu Huang,Qianzhen Zhang,Guozheng Yang,Deke Guo

  55. A GAIL Fine-Tuned LLM Enhanced Framework for Low-Resource Knowledge Graph Question Answering

    Zhiqiang Zhang,Liqiang Wen,Wen Zhao

  56. Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation

    Neng Kai Nigel Neo,Yeon-Chang Lee,Yiqiao Jin,Sang-Wook Kim,Srijan Kumar

  57. Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation

    Shiyuan Li,Yixin Liu,Qingfeng Chen,Geoffrey I. Webb,Shirui Pan

  58. Privacy-Preserving Graph Embedding based on Local Differential Privacy

    Zening Li,Rong-Hua Li,Meihao Liao,Fusheng Jin,Guoren Wang

  59. Spectral-Aware Augmentation for Enhanced Graph Representation Learning

    Kaiqi Yang,Haoyu Han,Wei Jin,Hui Liu

  60. Discovering Graph Generating Dependencies for Property Graph Profiling

    Larissa C. Shimomura,Nikolay Yakovets,George Fletcher

  61. Hierarchical Structure Construction on Hypergraphs

    Qi Luo,Wenjie Zhang,Zhengyi Yang,Dong Wen,Xiaoyang Wang,Dongxiao Yu,Xuemin Lin

  62. Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation

    Weizhi Zhang,Liangwei Yang,Zihe Song,Henry Peng Zou,Ke Xu,Liancheng Fang,Philip S. Yu

  63. Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation

    Guojun Liang,Prayag Tiwari,Sławomir Nowaczyk,Stefan Byttner

  64. Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks

    Jie Peng,Runlin Lei,Zhewei Wei

  65. Improving Message-Passing GNNs by Asynchronous Aggregation

    Jialong Chen,Tianchi Liao,Chuan Chen,Zibin Zheng

  66. Benchmarking Challenges for Temporal Knowledge Graph Alignment

    Weixin Zeng,Jie Zhou,Xiang Zhao

  67. Graph Local Homophily Network for Anomaly Detection

    Ronghui Guo,Minghui Zou,Sai Zhang,Xiaowang Zhang,Zhizhi Yu,Zhiyong Feng

  68. Efficient Pruned Top-K Subgraph Matching with Topology-Aware Bounds

    Linglin Yang,Yuqi Zhou,Yue Pang,Lei Zou

  69. Zero-shot Knowledge Graph Question Generation via Multi-agent LLMs and Small Models Synthesis

    Runhao Zhao,Jiuyang Tang,Weixin Zeng,Ziyang Chen,Xiang Zhao

  70. Revisit Orthogonality in Graph-Regularized MLPs

    Hengrui Zhang,Shen Wang,Vassilis N. Ioannidis,Soji Adeshina,Jiani Zhang,Xiao Qin,Christos Faloutsos,Da Zheng,George Karypis,Philip S. Yu

  71. FABLE: Approximate Butterfly Counting in Bipartite Graph Stream with Duplicate Edges

    Guozhang Sun,Yuhai Zhao,Yuan Li

  72. Understanding GNNs for Boolean Satisfiability through Approximation Algorithms

    Jan Hůla,David Mojžíšek,Mikoláš Janota

  73. NeutronCache: An Efficient Cache-Enhanced Distributed Graph Neural Network Training System

    Chu Zhao,Shengjie Dong,Yuhai Zhao,Yuan Li

  74. Embedding Knowledge Graphs in Function Spaces

    Louis Mozart Kamdem Teyou,Caglar Demir,Axel-Cyrille Ngonga Ngomo

  75. Distilling Large Language Models for Text-Attributed Graph Learning

    Bo Pan,Zheng Zhang,Yifei Zhang,Yuntong Hu,Liang Zhao

  76. Look Globally and Reason: Two-stage Path Reasoning over Sparse Knowledge Graphs

    Saiping Guan,Jiyao Wei,Xiaolong Jin,Jiafeng Guo,Xueqi Cheng

  77. Hierarchical Spatio-Temporal Graph Learning Based on Metapath Aggregation for Emergency Supply Forecasting

    Li Lin,Kaiwen Xia,Anqi Zheng,Shijie Hu,Shuai Wang

  78. PROSPECT: Learn MLPs on Graphs Robust against Adversarial Structure Attacks

    Bowen Deng,Jialong Chen,Yanming Hu,Zhiyong Xu,Chuan Chen,Tao Zhang

  79. Transformer Based Bayesian Network Embedding for Efficient Multiple Probabilistic Inferences

    Kun Yue,Zhiwei Qi,Liang Duan,Zhu Yang

  80. LLM-Empowered Few-Shot Node Classification on Incomplete Graphs with Real Node Degrees

    Yun Li,Yi Yang,Jiaqi Zhu,Hui Chen,Hongan Wang

  81. Exploring Robustness of GNN against Universal Injection Attack from a Worst-case Perspective

    Dandan Ni,Sheng Zhang,Cong Deng,Han Liu,Gang Chen,Minhao Cheng,Hongyang Chen

  82. Collaborative Fraud Detection on Large Scale Graph Using Secure Multi-Party Computation

    Xin Liu,Xiaoyu Fan,Rong Ma,Kun Chen,Yi Li,Guosai Wang,Wei Xu

  83. Breaking the Bottleneck on Graphs with Structured State Spaces

    Yunchong Song,Siyuan Huang,Jiacheng Cai,Xinbing Wang,Chenghu Zhou,Zhouhan Lin

AAAI-2024

  1. Attribute-missing Graph Clustering Network

    Tu, Wenxuan*; Guan, Renxiang; Zhou, Sihang; Ma, Chuan; Peng, Xin; Cai, Zhiping; Liu, Zhe; Cheng, Jieren; Liu, Xinwang

  2. Cell Graph Transformer for Nuclei Classification

    Lou, Wei; Li, Guanbin; Wan, Xiang; Li, Haofeng*

  3. Panoptic Scene Graph Generation with Semantics-prototype Learning

    Li, Li*; Ji, Wei; Wu, Yiming; Li, Mengze; QIN, YOU; Wei, Lina; Zimmermann, Roger

  4. A Transfer Approach Using Graph Neural Networks in Deep Reinforcement Learning

    Yang, Tianpei*; You, Heng; Hao, Jianye; Zheng, Yan; Taylor, Matthew E.

  5. SGFormer: Semantic Graph Transformer for Point Cloud-based 3D Scene Graph Generation

    Lv, Changsheng; Qi, Mengshi*; Li, Xia; Yang, Zhengyuan; Ma, Huadong

  6. Multi-Prototype Space Learning for Commonsense-based Scene Graph Generation

    Chen, Lianggangxu; Song, Youqi; Cai, Yiqing ; Lu, Jiale; Li, Yang; Xie, Yuan; Wang, Changbo; He, Gaoqi*

  7. Dynamic Sub-graph Distillation for Robust Semi- supervised Continual Learning

    Fan, Yan*; Wang, Yu; Zhu, Pengfei; Hu, Qinghua

  8. Multimodal Event Causality Reasoning with Scene Graph Enhanced Interaction Network

    Liu, Jintao*; wei, kaiwen; Liu, Chenglong

  9. MDGNN: Multi-relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction

    Qian, Hao*; Zhou, Hongting; Zhao, Qian; Chen, Hao; Yao, Hongxiang; Wang, Jingwei; Liu, Ziqi; Yu, Fei; Zhang, Zhiqiang; Zhou, Jun

  10. TextGT: A Double-View Graph Transformer on Text for Aspect-Based Sentiment Analysis

    Yin, Shuo*; Zhong, Guoqiang

  11. Identifiability of Direct Effects from Summary Causal Graphs

    Ferreira, Simon M*; Assaad, Charles K.

  12. Gramformer: Learning Crowd Counting via Graph-Modulated Transformer

    LIN, Hui; Ma, Zhiheng; Hong, Xiaopeng*; shangguan, qinnan; Meng, Deyu

  13. Hawkes-enhanced Spatial-Temporal Hypergraph Contrastive Learning based on Criminal Correlations

    Liang, Ke*; Zhou, Sihang; Liu, Meng; Liu, Yue; Tu, Wenxuan; Zhang, Yi; Fang, Liming; Liu, Zhe; Liu, Xinwang

  14. Rethinking Causal Relationships Learning in Graph Neural Networks

    Gao, Hang; chengyu, yao; Li, Jiangmeng; Si , Lingyu; Jin, Yifan; Wu, Fengge*; Zheng, Changwen; Liu, Huaping

  15. Propagation Tree is not Deep: Adaptive Graph Contrastive Learning Approach for Rumor Detection

    Cui, Chaoqun*; Jia, Caiyan

  16. Label Attentive Distillation for GNN-based Graph Classification

    Hong, Xiaobin*; Li, Wenzhong; Wang, Chaoqun; Lin, Mingkai; Lu, Sanglu

  17. A Non-parametric Graph Clustering Framework for Multi-view Data

    yu, shengju*; Wang, Siwei; Dong, Zhibin; Tu, Wenxuan; Liu, Suyuan; Lv, Zhao; Li, Pan; Wang, Miao; Zhu, En

  18. An Efficient Subgraph-inferring Framework for Large-scale Heterogeneous Graphs

    Zhou, Wei; Huang, Hong*; Shi, Ruize; Yin, Kehan khyin; Jin, Hai

  19. TREE-G: Decision Trees Contesting Graph Neural Networks

    Bechler-Speicher, Maya*; Globerson, Amir; Gilad- Bachrach, Ran

  20. TD$^2$-Net: Toward Denoising and Debiasing for Video Scene Graph Generation

    Lin, Xin*; Shi, Chong; Zhan, Yibing; Yang, Zuopeng; Wu, Yaqi; Tao, Dacheng

  21. ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection

    He, Junwei*; Xu, Qianqian; Jiang, Yangbangyan; Wang, Zitai; Huang, Qingming

  22. Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought

    Zheng, Li*; Fei, Hao; Li, Fei; Li, Bobo; Liao, Lizi; Ji, Donghong; Teng, Chong

  23. MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor- Enhanced Subgraphs

    Liang, Ke*; Meng, Lingyuan; Zhou, Sihang; Tu, Wenxuan; Wang, Siwei; Liu, Yue; Liu, Meng; Zhao, Long; Dong, Xiangjun; Liu, Xinwang

  24. HGE: Embedding Temporal Knowledge Graphs in a Product Space of Heterogeneous Geometric Subspaces

    Pan, Jiaxin*; Nayyeri, Mojtaba; Li, Yinan; Staab, Steffen

  25. Learning to Approximate Adaptive Kernel Convolution on Graphs

    Sim, Jaeyoon*; Jeon, Sooyeon; Choi, InJun; Wu, Guorong; Kim, Won Hwa

  26. Graph Context Transformation Learning for Progressive Correspondence Pruning

    Guo, Junwen; Xiao, Guobao*; Wang, Shiping; Yu, Jun

  27. Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks

    Liu, Ao*; Li, Wenshan; Li, Tao; Li, Beibei; Huang, Hanyuan; Zhou, Pan

  28. Parameterization of (Partial) Maximum Satisfiability Above Matching in a Variable- Clause Graph

    Alferov, Vasily; Bliznets, Ivan*; Brilliantov, Kirill

  29. Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking

    Gao, Yan; Xu, Haojun; Li, Jie; Wang, Nannan; Gao, Xinbo*

  30. SEA-GWNN: Simple and Effective Adaptive Graph Wavelet Neural Network

    Deb, Swakshar*; Rahman, Sejuti; Rahman, Shafin

  31. A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction

    Chao, Wen Shuo*; Qiu, Zhaopeng; Wu, Likang; Guo, Zhuoning; Zheng, Zhi; Zhu, Hengshu; Liu, Hao

  32. Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations

    Wu, Likang*; Qiu, Zhaopeng; Zheng, Zhi; Zhu, Hengshu; Chen, Enhong

  33. MGNet: Learning Correspondences via Multiple Graphs

    LUANYUAN, DAI; Du, Xiaoyu; Zhang, Hanwang; Tang, Jinhui*

  34. X-RefSeg3D: Enhancing Referring 3D Instance Segmentation via Structured Cross-Modal Graph Neural Networks

    Qian, Zhipeng*; Ma, Yiwei; Ji, Jiayi; Sun, Xiaoshuai

  35. WaveNet: Tackling Non-Stationary Graph Signals via Graph Spectral Wavelets

    Yang, Zhirui*; hu, yulan; Ouyang, Sheng; Liu, Jingyu; Wang, Shuqiang; Ma, Xibo; Wang, Wenhan; Su, Hanjing; Liu, Yong

  36. Kumaraswamy Wavelet for Heterophilic Scene Graph Generation

    Chen, Lianggangxu; Song, Youqi; Lin, Shaohui; Wang, Changbo; He, Gaoqi*

  37. Feature Transportation Improves Graph Neural Networks

    Eliasof, Moshe*; Haber, Eldad; Treister, Eran

  38. Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning

    Li, Longkang; Liang, Siyuan; Zhu, Zihao; Ding, Chris H.Q.; Zha, Hongyuan; Wu, Baoyuan*

  39. Improving Distinguishability of Class for Graph Neural Networks

    He, Dongxiao; Liu, Shuwei; Yu, Zhizhi*; Xu, Guangquan; Ge, Meng; Feng, Zhiyong

  40. Dynamic Reactive Spiking Graph Neural Network

    Zhao, Han; Yang, Xu; Deng, Cheng*; Yan, Junchi

  41. G^2SAM: Graph-Based Global Semantic Awareness Method for Multimodal Sarcasm Detection

    wei, yiwei*; Yuan, Shaozu; zhou, hengyang; Wang, Longbiao; Yan, Zhiling; Yang, Ruosong; Chen, Meng

  42. Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction

    Huang, Yufei*; Li, Siyuan; Wu, Lirong; Su, Jin; Lin, Haitao; Zhang, Odin; Liu, Zihan; Gao, Zhangyang; Zheng, Jiangbin; Li, Stan Z.

  43. Every Node is Different: Dynamically Fusing Self- Supervised Tasks for Attributed Graph Clustering

    Zhu, Pengfei; Wang, Qian; Wang, Yu*; Li, Jialu; Hu, Qinghua

  44. Graph Reasoning Transformers for Knowledge- Aware Question Answering

    Zhao, Ruilin; Zhao, Feng*; Hu, Liang; Xu, Guandong

  45. Towards Continual Knowledge Graph Embedding via Incremental Distillation

    Liu, Jiajun; Wenjun, Ke*; Wang, Peng; Shang, Ziyu; Jinhua, Gao; Li, Guozheng; Ji, Ke; Liu, Yanhe

  46. Patch-wise Graph Contrastive Learning for Image Translation

    Jung, Chanyong*; Kwon, Gihyun; Ye, Jong Chul

  47. CI-STHPAN: Pre-Trained Attention Network for Stock Selection with Channel-Independent Spatio-Temporal Hypergraph

    Xia, Hongjie; Ao, Huijie; Li, Long; Liu, Yu; Liu, Sen; Ye, Guangnan*; Chai, Hongfeng

  48. Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs

    Wienöbst, Marcel*; van der Zander, Benito; Liskiewicz, Maciej

  49. Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective

    Ji, Qirui; Li, Jiangmeng*; Hu, Jie; Wang, Rui; Zheng, Changwen; Xu, Fanjiang

  50. Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering

    Wen, Zichen*; Ling, Yawen; Ren, Yazhou; Wu, TianYi; Chen, Jianpeng; Pu, Xiaorong; Hao, Zhifeng; He, Lifang

  51. Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-view Clustering

    Pu, Jingyu*; Cui, Chenhang; Chen, Xinyue; Ren, Yazhou; Pu, Xiaorong; Hao, Zhifeng; Yu, Philip S; He, Lifang

  52. Robust Node Classification on Graph Data with Graph and Label Noise

    Zhu, Yonghua*; Feng, Lei; Deng, Zhenyun; Chen, Yang; Amor, Robert; Witbrock, Michael J

  53. A New Mechanism for Eliminating Implicit Conflict in Graph Contrastive Learning

    He, Dongxiao; Zhao, Jitao; Huo, Cuiying; Yongqi, Huang; Huang, Yuxiao*; Feng, Zhiyong

  54. COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems

    Tian, Hao*; Medya, Sourav; Ye, Wei

  55. Deep Contrastive Graph Learning with Clustering-Oriented Guidance

    Chen, Mulin*; Wang, Bocheng; Li, Xuelong

  56. Enhancing Multi-scale Diffusion Prediction via Sequential Hypergraphs and Adversarial Learning

    Jiao, Pengfei*; Chen, Hongqian; Bao, Qing; Zhang, Wang; Wu, Huaming

  57. Rethinking Graph Masked Autoencoders through Alignment and Uniformity

    Wang, Liang*; Tao, Xiang; Liu, Qiang; Wu, Shu; Wang, Liang

  58. Knowledge Graph Prompting for Multi- Document Question Answering

    Wang, Yu*; Lipka, Nedim; Rossi, Ryan A.; Siu, Alexa; Zhang, Ruiyi; Derr, Tyler

  59. Dual-channel Learning Framework for Drug-Drug Interaction Prediction via Relation-aware Heterogeneous Graph Transformer

    Su, Xiaorui; Hu, Pengwei; You, Zhu-Hong; Yu, Philip S; Hu, Lun*

  60. NodeMixup: Tackling Under-Reaching for Graph Neural Networks

    Lu, Weigang*; Guan, Ziyu; Zhao, Wei; Yang, Yaming; jin, long

  61. Neural Gaussian Similarity Modeling for Differential Graph Structure Learning

    Fan, Xiaolong*; Gong, Maoguo; Wu, Yue; Tang, Zedont; Liu, Jieyi

  62. Sterling: Synergistic Representation Learning on Bipartite Graphs

    Jing, Baoyu*; Yan, Yuchen; Ding, Kaize; Park, Chanyoung; Zhu, Yada; Liu, Huan; Tong, Hanghang

  63. Factorized Explainer for Graph Neural Networks

    Huang, Rundong; Shirani, Farhad; Luo, Dongsheng*

  64. Hyperbolic Graph Diffusion Model

    Wen, Lingfeng; TANG, XUAN; Ouyang, Mingjie; Shen, Xiangxiang; Yang, Jian; Zhu, Daxin; Chen, Mingsong; Wei, Xian*

  65. Union Subgraph Neural Networks

    Xu, Jiaxing*; Zhang, Aihu; Bian, Qingtian; Dwivedi, Vijay Prakash; Ke, Yiping

  66. GOODAT: Towards Test-time Graph Out-of- Distribution Detection

    Wang, Luzhi*; Jin, Di; Zhang, He; Liu, Yixin; He, Dongxiao; Wang, Wenjie; Pan, Shirui; Chua, Tat- Seng

  67. DHGCN: Dynamic Hop Graph Convolution Network for Self-supervised Point Cloud Learning

    Jiang, Jincen; Zhao, Lizhi; Lu, Xuequan; Hu, Wei; Razzak, Imran; wang, meili*

  68. HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors

    Zhang, Heng-Kai*; Zhang, Yi-Ge; Zhou, Zhi; Li, Yu- Feng

  69. Temporal Graph Contrastive Learning for Sequential Recommendation

    Zhang, Shengzhe*; Chen, Liyi; Wang, Chao; Li, Shuangli; Xiong, Hui

  70. End-to-End Verification for Subgraph Solving

    Gocht, Stephan ; McCreesh, Ciaran*; Myreen, Magnus; Nordström, Jakob; Oertel, Andy; Tan, Yong Kiam

  71. An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction

    Zaratiana, Urchade*; Tomeh, Nadi; Holat, Pierre; Charnois, Thierry

  72. Beyond Atomic Facts: Modeling Relationships between Facts for Knowledge Graph Reasoning

    Xiong, Bo*; Nayyeri, Mojtaba; Luo, Linhao; Wang, Zihao; Pan, Shirui; Staab, Steffen

  73. Open-Set Graph Domain Adaptation via Separate Domain Alignment

    Wang, Yu; Zhu, Ronghang*; Ji, Pengsheng; Li, Sheng

  74. Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning

    Sun, Li*; Huang, Zhenhao; Wang, Zixi; Wang, Feiyang; Peng, Hao; Yu, Philip S

  75. A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs

    Yang, Sikun*; Zha, Hongyuan

  76. SURER: Structure-Adaptive Unified Graph Neural Network for Multi-view Clustering

    Wang, Jing; Feng, Songhe*; Lyu, Gengyu; Yuan, Jiazheng

  77. TEILP: Time prediction over knowledge graphs via logical reasoning

    Xiong, Siheng*; Yang, Yuan; Payani, Ali; Kerce, James C; Fekri, Faramarz

  78. Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations

    Huang, Yufeng*; Tang, Jiji; Chen, Zhuo; Zhang, Rongsheng; Zhang, Xinfeng; Chen, Weijie; Zhao, Zeng; Zhao, Zhou; Lv, Tangjie; Hu, Zhipeng; Zhang, Wen

  79. Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance

    Wang, Yingheng*; Kong, Shufeng; Gregoire, John; Gomes, Carla P

  80. Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution

    Su, Yifan*; Veerapaneni, Rishi; Li, Jiaoyang

  81. Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks

    Qiu, Chenyang*; Nan, Guoshun; Xiong, Tianyu; Deng, Wendi; Wang, Di; Teng, Zhiyang; Sun, Lijuan; Cui, Qimei; Tao, Xiaofeng

  82. Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction

    Lu, Kangkang; yu, yanhua*; Fei, Hao; Li, Xuan; Yang, Zixuan; Guo, Zirui; Liang, Meiyu; Yin, Mengran; Chua, Tat-Seng

  83. Graph Contextual Contrasting for Multivariate Time Series Classification

    Wang, Yucheng*; Xu, Yuecong; Yang, Jianfei; Wu, Min; Li, Xiaoli; Xie, Lihua; Chen, Zhenghua

  84. ECHO-GL: Earnings Calls-driven Heterogeneous Graph Learning for Stock Movement Prediction

    Liu, Mengpu*; Zhu, Mengying; Wang, Xiuyuan; Ma, Guofang; Yin, Jianwei; Zheng, Xiaolin

  85. Deep Semantic Graph Transformer for Multi- view 3D Human Pose Estimation

    Zhang, Lijun*; zhou, kangkang; Lu, Feng; Zhou, Xiang-Dong; Shi, Yu

  86. FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

    Yang, Cheng; Liu, Jixi*; Yan, Yunhe; Shi, Chuan

  87. LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement

    Peng, Renyuan; Cai, Xinyue; Xu, Hang; Lu, Jiachen; Wen, Feng; Zhang, Wei; Zhang, Li*

  88. Graph Neural Networks with Soft Association between Topology and Attribute

    Yang, Yachao*; Sun, Yanfeng; Wang, Shaofan; Guo, Jipeng; Gao, Junbin; Ju, Fujiao; Yin, Baocai

  89. No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation

    Agrawal, Nimesh*; Sirohi, Anuj Kumar; Kumar, Sandeep Prof.; Jayadeva, Jayadeva

  90. KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding

    Chen, Zhen; Zhang, Dalin; Feng, Shanshan; Chen, Kaixuan; Chen, Lisi; Han, Peng; Shang, Shuo*

  91. SAT-based Algorithms for Regular Graph Pattern Matching

    Terra-Neves, Miguel*; Amaral, José; Lemos, Alexandre; Quintino, Rui Dias; Resende, Pedro; Alegria, Antonio

  92. ReGCL: Rethinking Message Passing in Graph Contrastive Learning

    Ji, Cheng*; Huang, Zixuan zi; Sun, Qingyun; Peng, Hao; Fu, Xingcheng; Li, Qian; Li, Jianxin

  93. Multimodal Graph Neural Architecture Search Under Distribution Shifts

    Cai, Jie*; Wang, Xin; Li, Haoyang; Zhang, Ziwei; Zhu, Wenwu

  94. Self-Interpretable Graph Learning with Sufficient and Necessary Explanations

    Deng, Jiale; Shen, Yanyan*

  95. Graph-Shot Prompting: Solving Elaborate Problems in Large Language Models

    Besta, Maciej*; Blach, Nils; Kubicek, Ales; Gerstenberger, Robert; Podstawski, Michal; Gianinazzi, Lukas; Gajda, Joanna; Lehmann, Tomasz; Niewiadomski, Hubert; Nyczyk, Piotr; Hoefler, Torsten

  96. SpaceGTN: A Time-Agnostic Graph Transformer Network for Handwritten Diagram Recognition and Segmentation

    hu, haoxiang*; Gao, Cangjun; Li, YaoKun; Deng, Xiaoming; Lai, Yukun; Ma, Cuixia; Liu, Yong-Jin; Wang, Hongan

  97. Editing Language Model-based Knowledge Graph Embeddings

    Cheng, Siyuan; Zhang, Ningyu*; Tian, Bozhong; Chen, Xi; Liu, Qingbin; Chen, Huajun

  98. Barely Supervised Learning for Graph-based Fraud Detection

    Yu, Hang*; Liu, Zhengyang; Luo, Xiangfeng

  99. Federated Graph Learning under Domain Shift with Generalizable Prototypes

    Wan, Guancheng; Huang, Wenke; Ye, Mang*

  100. CK12: A Rounded K12 Knowledge Graph Based Benchmark for Chinese Holistic Cognition Evaluation

    You, Weihao*; Wang, Pengcheng; Li, Changlong; ji, zhilong; Bai, Jinfeng

  101. GAMC: An Unsupervised Method for Fake News Detection using Graph Autoencoder with Masking

    Yin, Shu; Zhu, Peican; Wu, Lianwei; Gao, Chao*; Wang, Zhen

  102. GraFITi: Graphs for Forecasting Irregularly Sampled Time Series

    Yalavarthi, Vijaya Krishna*; Madhusudhanan, Kiran; Scholz, Randolf; Ahmed, Nourhan; Burchert, Johannes; Jawed, Shayan; Born, Stefan; Schmidt-Thieme, Lars

  103. DAG-Aware Variational Autoencoder for Social Propagation Graph Generation

    Hou, Dongpeng; Gao, Chao*; Li, Xuelong; Wang, Zhen

  104. ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network

    Liu, Ruyue; Yin, Rong*; Liu, Yong; Wang, Weiping

  105. A Goal Interaction Graph Planning Framework for Conversational Recommendation

    Zhang, Xiaotong*; jia, xuefang; Liu, Han; Liu, Xinyue; Zhang, Xianchao

  106. Continuous-time Graph Representation with Sequential Survival Process

    Celikkanat, Abdulkadir*; Nakis, Nikolaos; Mørup, Morten

  107. Emotion Rendering for Conversational Speech Synthesis with Heterogeneous Graph-Based Context Modeling

    Liu, Rui*; Hu, Yifan; Ren, Yi; Yin, Xiang; Li, Haizhou

  108. Coupling Graph Neural Networks with Non- Integer Order Dynamics: A Robustness Study

    ZHAO, KAI*; Kang, Qiyu; Song, Yang; XIE, YIHANG; ZHAO, YANAN; Wang, Sijie; She, Rui; Tay, Wee Peng

  109. Dynamic Semantic-based Spatial Graph Convolution Network for Skeleton-based Human Action Recognition

    Xie, Jianyang*; Meng, Yanda; Zhao, Yitian; Nguyen, Anh; yang, xiaoyun; Zheng, Yalin

  110. Span Graph Transformer for Document-level Named Entity Recognition

    Mao, Hongli*; Mao, Xian-Ling; Tang, Hanlin; Shang, Yu-Ming; Huang, Heyan

  111. KGDM: A Diffusion Model to Capture Multiple Relation Semantics for Knowledge Graph Embedding

    long, xiao; Zhuang, Liansheng*; Li, Aodi; Wei, Jiuchang; Li, Houqiang; wang, shafei

  112. Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables

    Gong, Haisong*; Xu, Weizhi; Wu, Shu; Liu, Qiang; Wang, Liang

  113. BOK-VQA: Bilingual Outside Knowledge-based Visual Question Answering via Graph Representation Pretraining

    Kim, Minjun; Song, SeungWoo; Lee, Youhan; Jang, Haneol; Lim, KyungTae*

  114. Optimal Quasi-clique: Hardness, equivalence with Densest-$k$-Subgraph, and quasi- partitioned community mining

    Konar, Aritra*; Sidiropoulos, Nicholas D

  115. KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs

    Liu, Ruoqi*; Wu, Lingfei; Zhang, Ping

  116. Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs

    Lee, Dongjin; Lee, Juho; Shin, Kijung*

  117. Learning Efficient and Robust Multi-agent Communication via Graph Information Bottleneck

    Ding, Shifei*; du, wei; Ding, Ling; Guo, Lili; Zhang, Jian

  118. TopoGCL: Topological Graph Contrastive Learning

    Chen, Yuzhou*; Frias, Jose; Gel, Yulia R.

  119. Spatio-Temporal Fusion for Human Action Recognition via Joint Trajectory Graph

    Zheng, Yaolin; Huang, Hongbo*; wang, xiuying; Yan, Xiaoxu; Xu, Longfei

  120. Towards the disappearing truth: Fine-grained joint causal influences learning with hidden variable-driven causal hypergraphs

    Zhu, Kun*; Zhao, Chunhui

  121. Mixed Geometry Message and Trainable Convolutional Attention Network for Knowledge Graph Completion

    Shang, Bin; Zhao, Yinliang*; Liu, Jun; Wang, Di

  122. GCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction

    Wang, Xinshun; Cui, Qiongjie; Chen, Chen; Liu, Mengyuan*

  123. Hypergraph Neural Architecture Search

    Lin, Wei; Peng, Xu; Yu, Zhengtao; Jin, Taisong*

  124. Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation

    Liu, Jing*; Sun, Lele; Nie, Weizhi; Jing, Peiguang; Su, Yu-ting

  125. ROG_PL: Robust Open-Set Graph Learning via Region-based Prototype learning

    ZHANG, QIN*; Lu, Jiexin; Li, Xiaowei; Qiu, Liping; Pan, Shirui; Chen, Xiaojun; Chen, Junyang

  126. DGCLUSTER: A Neural Framework For Attributed Graph Clustering via Modularity Maximization

    Bhowmick, Aritra*; Kosan, Mert; Huang, Zexi; Singh, Ambuj K; Medya, Sourav

  127. Design Graph Guided Element Importance- aware Layout generation with Multi-modality Cascade Transformer

    Zhang, Qiuyun; Guo, Bin*; Yao, Lina; Wang, Hao; Qiao, Xiaotian; Zhang, Ying; Yu, Zhiwen

  128. Full-body Motion Reconstruction with Sparse Sensing from Graph Perspective

    Yao, Feiyu*; Wu, Zongkai; Yi, Li

  129. LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs

    Wang, Yan; Chu, Zhixuan*; Ouyang, Xin; Wang, Simeng; hao, hongyan; Shen, Yue; Gu, Jinjie; Xue, Siqiao; Zhang, James Y; Cui, Qing; li, longfei; Zhou, Jun; Li, Sheng

  130. GIN-SD: Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion

    Cheng, Le; Zhu, Peican*; Tang, Keke; Gao, Chao; Wang, Zhen

  131. Spectral-based Graph Neutral Networks for Complementary Item Recommendation

    Luo, Haitong*; Meng, Xuying; Wang, Suhang; Cao, Hanyun; zhang, weiyao wei; Wang, Yequan; Zhang, Yujun

  132. Self-supervised Multi-modal Knowledge Graph Contrastive Hashing for Cross-Modal Search

    Liang, Meiyu*; Du, Junping; Liang, Zhengyang; Xing, Yongwang; wei, huang; Xue, Zhe

  133. LGMRec: Local and Global Graph Learning for Multimodal Recommendation

    Guo, Zhiqiang; Li, Jianjun*; Li, Guohui; Wang, Chaoyang; Shi, Si; Ruan, Bin

  134. Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting

    Guan, Xinyan*; liu, yanjiang; Lin, Hongyu; Lu, Yaojie; He, Ben; Han, Xianpei; Sun, Le

  135. Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs

    Fiorini, Stefano*; Coniglio, Stefano; Ciavotta, Michele; Messina, Enza

  136. Knowledge Graph Error Detection with Contrastive Confidence Adaption

    Liu, Xiangyu*; Liu, Yang; Hu, Wei

  137. Graph-based Prediction and Planning Policy Network (GP3Net) for scalable self-driving in dynamic environments using Deep Reinforcement Learning

    Chowdhury, Jayabrata*; Shivaraman, Venkataramanan; Sundaram, Suresh; PB, Sujit

  138. Graph Contrastive Invariant Learning from the Causal Perspective

    Wang, Xiao; Mo, Yanhu*; Fan, Shaohua; Shi, Chuan

  139. Discrete Cycle-Consistency based Unsupervised Deep Graph Matching

    Tourani, Siddharth*; Khan, Muhammad Haris; Rother, Carsten; Savchynskyy, Bogdan

  140. Residual Hyperbolic Graph Convolution Networks

    Xue, Yangkai; Dai, Jindou; Lu, Zhipeng*; Wu, Yuwei; Jia, Yunde

  141. Tensorized Label Learning on Anchor Graph

    Li, Jing; Gao, Quanxue; Wang, Qianqian*; Xia, Wei

  142. Rethinking Propagation for Unsupervised Graph Domain Adaptation

    Liu, Meihan*; Fang, Zeyu; Zhang, Zhen; Gu, Ming; Zhou, Sheng; Wang, Xin; Bu, Jiajun

  143. Modeling Knowledge Graphs with Composite Reasoning

    Cui, Wanyun*; Zhang, Linqiu

  144. A Generalized Neural Diffusion Framework on Graphs

    Li, Yibo*; Wang, Xiao; Liu, Hongrui; Shi, Chuan

  145. Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity

    Hoang, Van Thuy*; Lee, O-Joun

  146. Adaptive Graph Learning for Multimodal Conversational Emotion Detection

    Tu, Geng; Xie, Tian; Liang, Bin; Wang, Hongpeng; Xu, Ruifeng*

  147. Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion

    Yan, Yuguang; Chen, Yuanlin Chen; Wang, Shibo; Wu, Hanrui; Cai, Ruichu*

  148. Coreference Graph Guidance for Mind-Map Generation

    Zhang, Zhuowei; Hu, Mengting*; Bai, Yinhao; Zhang, Zhen

  149. You Only Read Once: Constituency-Oriented Relational Graph Convolutional Network for Multi-Aspect Multi-Sentiment Classification

    Zheng, Yongqiang; li, xia*

  150. DiG-In-GNN: Discriminative Feature Guided GNN-based Fraud Detector against Inconsistencies in Multi-Relation Fraud Graph

    Zhang, Jinghui; Xu, Zhengjia*; Lv, Dingyang; Shi, Zhan; Shen, Dian; Jin, Jiahui; Dong, Fang

  151. Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting

    Kong, Weiyang; Guo, Ziyu; Liu, Yubao*

  152. Limited Query Graph Connectivity Test

    Guo, Mingyu*; Li, Jialiang; Neumann, Aneta; Neumann, Frank; Nguyen, Hung

  153. Beyond Entities: A Large-Scale Multi-Modal Knowledge Graph with Triplet Fact Grounding

    Liu, Jingping*; Zhang, Mingchuan; Li, Weichen; Wang, Chao; Li, Shuang; Jiang, Haiyun; Jiang, Sihang; Xiao, Yanghua; Chen, Yunwen

  154. Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery

    YAN, Pengwei; Song, Kaisong; Jiang, Zhuoren*; Kang, Yangyang; lin, tianqianjin; Sun, Changlong; Liu, Xiaozhong

  155. Dependency Structure-Enhanced Graph Attention Networks for Event Detection

    Wan, Qizhi*; wan, Changxuan; Xiao, Keli; Lu, Kun; Li, Chenliang; Liu, Xiping; Liu, Dexi

  156. GLDL: Graph Label Distribution Learning

    Jin, Yufei; Gao, Richard; He, Yi; Zhu, Xingquan*

  157. Graph Invariant Learning with Subgraph Co- mixup for Out-Of-Distribution Generalization

    Jia, Tianrui*; Li, Haoyang; Yang, Cheng; Tao, Tao; Shi, Chuan

  158. Data-augmented Curriculum Graph Neural Architecture Search Under Distribution Shifts

    Yao, Yang*; Wang, Xin; Qin, Yijian; Zhang, Ziwei; Zhu, Wenwu; Mei, Hong

  159. Poincar'e Differentially Private for Hierarchy- aware Graph Emebedding

    Wei, Yuecen*; Yuan, Haonan; Fu, Xingcheng; Sun, Qingyun; Peng, Hao; Li, Xianxian; Hu, Chunming

  160. Recurrent Graph Neural Networks and Their Connections to Bisimulation and Logic

    Pflüger, Maximilian*; Tena Cucala, David J; Kostylev, Egor V.

  161. Improved Graph Contrastive Learning for Short Text Classification

    Liu, Yonghao; Huang, Lan; Giunchiglia, Fausto; Feng, Xiaoyue*; Guan, Renchu

  162. Hypergraph-Guided Disentangled Spectrum Transformer Networks for Near-Infrared Facial Expression Recognition

    Luo, Bingjun*; Wang, Haowen; Wang, Jinpeng; Zhu, Junjie; Zhao, Xibin ; Gao, Yue

  163. Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representation

    Zhang, Zhaofan; Xiao, Yanan; Jiang, Lu; Yang, Dingqi; Yin, Minghao; Wang, Pengyang*

  164. Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics

    Chen, Lanlan; WU, KAI*; Lou, Jian; Liu, Jing

  165. Graph Neural Prompting for Question Answering with Large Language Models

    Tian, Yijun; Song, Huan*; Wang, Zichen; Wang, Haozhu; Hu, Ziqing; Wang, Fang; Chawla, Nitesh; Xu, Panpan

  166. Revisiting Graph-based Fraud Detection in Sight of Heterophily and Spectrum

    Xu, Fan mark*; Wang, Nan; Wu, Hao; Wen, Xuezhi; Zhao, Xibin; Wan, Hai

  167. Towards Effective and General Graph Unlearning via Mutual Evolution

    Li, Xunkai*; Zhao, Yulin; Wu, Zhengyu; Zhang, Wentao; Li, Ronghua; Wang, Guoren

  168. Explainable Origin-Destination Crowd Flow Interpolation via Variational Multi-modal Recurrent Graph Auto-Encoder

    Zhou, Qiang; Lu, Xinjiang*; Gu, Jingjing; Zheng, Zhe; Jin, Bo; Zhou, Jingbo

  169. Embedded Feature Selection on Graph-based Multi-view Clustering

    Li, Guangfei; Yang, Haizhou; Gao, Quanxue; Wang, Qianqian*; Zhao, Wenhui

  170. MKG-FENN: A Multimodal Knowledge Graph Fused End-to-end Neural Network for Accurate Drug–Drug Interaction Prediction

    Wu, Di*; wu, sun; He, Yi; Chen, Zhong; Luo, Xin

  171. Learning to Reweight for Generalizable Graph Neural Network

    Chen, Zhengyu*; Xiao, Teng ; Kuang, Kun; Lv, Zheqi; Zhang, Min; Yang, Jinluan; Lu, Chengqiang; Yang, Hongxia; Wu, Fei

  172. Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks

    Huang, Renhong; Xu, Jiarong*; Jiang, Xin; Pan, Chenglu; Yang, Zhiming; Wang, Chunping; Yang, Yang

  173. Towards Fair Graph Federated Learning via Incentive Mechanisms

    Pan, Chenglu; Xu, Jiarong*; Yu, Yue; Yang, Ziqi; Wu, Qingbiao; Wang, Chunping; CHEN, Lei; Yang, Yang

  174. Value at Adversarial Risk: A Graph Defense Strategy Against Cost-Aware Attacks

    Liao, Junlong; Fu, Wenda; Wang, Cong; Wei, Zhongyu; Xu, Jiarong*

  175. A Joint Framework with Heterogeneous- Relation-Aware Graph and Multi-Channel Label Enhancing Strategy for Event Causality Extraction

    Pu, Ruili; Li, Yang; Zhao, Jun; Wang, Suge*; Li, Deyu; Liao, Jian; Zheng, Jianxing

  176. Bayesian Inference with Complex Knowledge Graph Evidence

    Toroghi, Armin*; Sanner, Scott

  177. Structural Information Enhanced Graph Representation for Link Prediction

    Shi, Lei*; Hu, Bin; Zhao, Deng; He, Jianshan; Zhang, Zhiqiang; Zhou, Jun

  178. Anchoring Path for Inductive Relation Prediction in Knowledge Graphs

    Su, Zhixiang*; Wang, Di; Miao, Chunyan; Cui, Lizhen

  179. R3CD: Scene Graph to Image Generation with Relation-aware Compositional Contrastive Control Diffusion

    Liu, Jinxiu*; Liu, Qi

  180. HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning

    Yu, Xingtong*; Fang, Yuan; Liu, Zemin; Zhang, Xinming

  181. Structural Entropy Based Graph Structure Learning for Node Classification

    Duan, Liang; xiang, chen; Wenjie, Liu; Liu, Daliang; Yue, Kun*; Li, Angsheng

  182. SimCalib: Graph Neural Network Calibration based on Similarity Between Nodes

    Tang, Boshi*; Wu, Zhiyong; Wu, Xixin; Huang, Qiaochu; Chen, Jun; Lei, Shun; Meng, Helen

  183. A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks

    Zhao, Zhe; Wang, Pengkun; Wen , HaiBin; Zhang, Yudong; Zhou, Zhengyang ; Wang, Yang*

  184. Fully-Connected Spatial-Temporal Graph for Multivariate Time Series Data

    Wang, Yucheng*; Xu, Yuecong; Yang, Jianfei; Wu, Min; Li, Xiaoli; Xie, Lihua; Chen, Zhenghua

  185. Data Augmented Graph Neural Networks for Personality Detection

    Zhu, Yangfu; Xia, Yue; Li, Meiling; Zhang, Tingting; Wu, Bin*

  186. LAFA: Multimodal Knowledge Graph Completion with Link Aware Fusion and Aggregation

    Shang, Bin; Zhao, Yinliang*; Liu, Jun; Wang, Di

  187. Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns

    Sun, Yifei*; Zhu, Qi; Yang, Yang; Wang, Chunping; Fan, Tianyu; Zhu, Jiajun; CHEN, Lei

  188. Complete Neural Networks for Complete Euclidean Graphs

    hordan, snir*; Amir, Tal; Dym, Nadav; Gortler, Steven

  189. Progressive Distillation based on Masked Generation Feature Method for Knowledge Graph Completion

    Fan, Cunhang*; Chen, Yujie; Xue, Jun; kong, yonghui; tao, jianhua; lv, zhao

  190. Dynamic Spiking Graph Neural Networks

    Nan, Yin*; Wang, Mengzhu; Chen, Zhenghan; De Masi, Giulia; Xiong, Huan; Gu, Bin

  191. G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks

    Gui, Anchun*; Ye, Jinqiang; Xiao, Han

  192. Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes

    Huang, Yiming*; Zeng, Yujie; Wu, Qiang; Lü, Linyuan

  193. Finite-Time Frequentist Regret Bounds of Multi- Agent Thompson Sampling on Sparse Hypergraphs

    Jin, Tianyuan*; Hsu, Hao-Lun; Chang, William; Xu, Pan

  194. Unknown-Aware Graph Regularization for Robust Semi-Supervised Learning from Uncurated Data

    Kong, Heejo*; Kim, Suneung; Kim, Ho-Joong; Lee, Seong-Whan

  195. A Graph Dynamics Prior for Relational Inference

    Pan, Liming*; Shi, Cheng; Dokmanic, Ivan

  196. Towards Streaming Spatial-Temporal Graph Learning: A Decoupled Perspective

    Wang, Binwu; Wang, Pengkun; Zhang, Yudong; Wang, Xu; Zhou, Zhengyang ; Bai, Lei; Wang, Yang*

  197. Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning

    Li, Jiangmeng; Jin, Yifan; Gao, Hang; Qiang, Wenwen*; Zheng, Changwen; Sun, Fuchun

  198. Scores for Learning Discrete Causal Graphs with Unobserved Confounders

    Bellot, Alexis*; Zhang, Junzhe; Bareinboim, Elias

  199. Provably Powerful Graph Neural Networks for Directed Multigraphs

    Egressy, Beni*; von Niederhäusern, Luc; Blanuša, Jovan; Altman, Erik; Wattenhofer, Roger; Atasu, Kubilay

  200. Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media

    Hebert, Liam*; Sahu, Gaurav; Guo, Yuxuan; Sreenivas, Nanda Kishore; Golab, Lukasz; Cohen, Robin

  201. Graph Bayesian Optimization for Multiplex Influence Maximization

    Yuan, Zirui; Shao, Minglai*; Chen, Zhiqian

  202. Multiple-Source Localization from a Single- Snapshot Observation Using Graph Bayesian Optimization

    Zhang, Zonghan*; Zhang, Zijian; Chen, Zhiqian

  203. T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking

    Nair, Pratheeksha*; Liu, Javin; Vajiac, Catalina; Olligschlaeger, Andreas; Chau, Duen Horng; Cazzolato, Mirela; Jones, Cara; Faloutsos, Christos; Rabbany, Reihaneh

  204. Fair Graph Learning Using Constraint-aware Priority Adjustment and Graph Masking in River Networks

    He, Erhu*; Xie, Yiqun; Sun, Alexander Y; Zwart, Jacob; Yang, Jie; Jin, Zhenong; Wang, Yang; Karimi, Hassan; Jia, Xiaowei

  205. Physics-Informed Graph Neural Networks for Water Distribution Systems

    Ashraf, Inaam*; Strotherm, Janine; Hermes, Luca; Hammer, Barbara

  206. Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media

    Hebert, Liam*; Sahu, Gaurav; Guo, Yuxuan; Sreenivas, Nanda Kishore; Golab, Lukasz; Cohen, Robin

  207. Graph Bayesian Optimization for Multiplex Influence Maximization

    Yuan, Zirui; Shao, Minglai*; Chen, Zhiqian

  208. Multiple-Source Localization from a Single- Snapshot Observation Using Graph Bayesian Optimization

    Zhang, Zonghan*; Zhang, Zijian; Chen, Zhiqian

  209. T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking

    Nair, Pratheeksha*; Liu, Javin; Vajiac, Catalina; Olligschlaeger, Andreas; Chau, Duen Horng; Cazzolato, Mirela; Jones, Cara; Faloutsos, Christos; Rabbany, Reihaneh

  210. Fair Graph Learning Using Constraint-aware Priority Adjustment and Graph Masking in River Networks

    He, Erhu*; Xie, Yiqun; Sun, Alexander Y; Zwart, Jacob; Yang, Jie; Jin, Zhenong; Wang, Yang; Karimi, Hassan; Jia, Xiaowei

  211. Physics-Informed Graph Neural Networks for Water Distribution Systems

    Ashraf, Inaam*; Strotherm, Janine; Hermes, Luca; Hammer, Barbara

  212. PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Signal Delay Learning and Attentional Cell Modeling

    Zhong, Ruizhe*; Ye, Junjie; Tang, Zhentao; Kai, Shixiong; Yuan, Mingxuan; Hao, Jianye; Yan, Junchi

  213. DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud Detection

    Duan, Mingjiang; Zheng, Tongya; Gao, Yang; Wang, Gang; Feng, Zunlei*; Wang, Xinyu

  214. AdapterGNN: Parameter-Efficient Fine-Tuning Improves Generalization in GNNs

    Li, Shengrui; Han, Xueting*; Bai, Jing

  215. DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems

    Wang, Bowen*; Liang, Chen; Wang, Jiaze; Qiu, Jiezhong; Liu, Furui; HAO, SHAOGANG; Li, Dong; Chen, Guangyong; Zou, Xiaolong; Heng, Pheng- Ann

  216. Prot2Text: Multimodal Protein’s Function Generation with GNNs and Transformers

    Abdine, Hadi*; Chatzianastasis, Michail; Bouyioukos, Costas; Vazirgiannis, Michalis

  217. Improving GNN Calibration with Discriminative Ability: Insights and Strategies

    Fang, Yujie; Li, Xin*; Chen, QIanyu; Wang, Mingzhong

  218. Stratified GNN Explanations through Sufficient Expansion

    Ji, Yuwen*; Shi, Lei; liu, zhimeng; Wang, Ge

  219. Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-smoothness in Deep GNNs

    Li, Jin; Zhang, Qirong; Xu, Shuling; Chen, Xinlong; Guo, Longkun l; Fu, Yang-Geng*

ICLR-2024

  1. Graph Neural Networks for Learning Equivariant Representations of Neural Networks.

    Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, David W. Zhang

  2. GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations.

    Zaishuo Xia, Han Yang, Binghui Wang, Jinyuan Jia

  3. Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness.

    Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang

  4. Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision.

    Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen

  5. PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters.

    Jingyu Chen, Runlin Lei, Zhewei Wei

  6. SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases.

    Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong

  7. Online GNN Evaluation Under Test-time Graph Distribution Shifts.

    Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan

  8. Graph Metanetworks for Processing Diverse Neural Architectures.

    Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas

  9. Hybrid Directional Graph Neural Network for Molecules.

    Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Yinghui Xu, Yuan Qi, Furao Shen

  10. GTMGC: Using Graph Transformer to Predict Molecule's Ground-State Conformation.

    Guikun Xu, Yongquan Jiang, PengChuan Lei, Yan Yang, Jim Chen

  11. Mayfly: a Neural Data Structure for Graph Stream Summarization.

    Yuan Feng, Yukun Cao, Hairu Wang, Xike Xie, S. Kevin Zhou

  12. Graphical Multioutput Gaussian Process with Attention.

    Yijue Dai, Wenzhong Yan, Feng Yin

  13. Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND.

    Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji, Xuhao Li, Wenfei Liang, Yang Song, Wee Peng Tay

  14. Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks.

    Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia

  15. MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy.

    Yan Sun, Jicong Fan

  16. A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs.

    Thien Le, Luana Ruiz, Stefanie Jegelka

  17. One For All: Towards Training One Graph Model For All Classification Tasks.

    Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang

  18. InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior.

    Chenguo Lin, Yadong Mu

  19. Rethinking and Extending the Probabilistic Inference Capacity of GNNs.

    Tuo Xu, Lei Zou

  20. Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks.

    Kesen Zhao, Liang Zhang

  21. Mirage: Model-agnostic Graph Distillation for Graph Classification.

    Mridul Gupta, Sahil Manchanda, Hariprasad Kodamana, Sayan Ranu

  22. Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability.

    Zehao Dong, Muhan Zhang, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen

  23. Graph Parsing Networks.

    Yunchong Song, Siyuan Huang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin

  24. Partitioning Message Passing for Graph Fraud Detection.

    Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen

  25. GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks.

    Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer

  26. Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning.

    Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi

  27. Deceptive Fairness Attacks on Graphs via Meta Learning.

    Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong

  28. Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World.

    Chunshu Wu, Ruibing Song, Chuan Liu, Yunan Yang, Ang Li, Michael C. Huang, Tong Geng

  29. Uncertainty-aware Graph-based Hyperspectral Image Classification.

    Linlin Yu, Yifei Lou, Feng Chen

  30. Graph Transformers on EHRs: Better Representation Improves Downstream Performance.

    Raphael Poulain, Rahmatollah Beheshti

  31. Structural Fairness-aware Active Learning for Graph Neural Networks.

    Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada

  32. Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation.

    Jaemin Cho, Yushi Hu, Jason M. Baldridge, Roopal Garg, Peter Anderson, Ranjay Krishna, Mohit Bansal, Jordi Pont-Tuset, Su Wang

  33. Counting Graph Substructures with Graph Neural Networks.

    Charilaos I. Kanatsoulis, Alejandro Ribeiro

  34. Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning.

    Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel C. Castro, Daniel C. Alexander

  35. Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs.

    Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Manish Singh, Toyotaro Suzumura

  36. Forward Learning of Graph Neural Networks.

    Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed

  37. NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks.

    Wenxi Wang, Yang Hu, Mohit Tiwari, Sarfraz Khurshid, Kenneth L. McMillan, Risto Miikkulainen

  38. VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections.

    Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long

  39. GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries.

    Xiaoqi Wang, Han-Wei Shen

  40. Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations.

    Giovanni de Felice, Andrea Cini, Daniele Zambon, Vladimir V. Gusev, Cesare Alippi

  41. Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network.

    Tianze Luo, Zhanfeng Mo, Sinno Jialin Pan

  42. AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ.

    Jonas Belouadi, Anne Lauscher, Steffen Eger

  43. Efficient Subgraph GNNs by Learning Effective Selection Policies.

    Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron

  44. MixSATGEN: Learning Graph Mixing for SAT Instance Generation.

    Xinyan Chen, Yang Li, Runzhong Wang, Junchi Yan

  45. PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation.

    Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian, Wentao Liu

  46. A Differentially Private Clustering Algorithm for Well-Clustered Graphs.

    Weiqiang He, Hendrik Fichtenberger, Pan Peng

  47. Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks.

    Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström

  48. HiGen: Hierarchical Graph Generative Networks.

    Mahdi Karami

  49. Mitigating Emergent Robustness Degradation while Scaling Graph Learning.

    Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang

  50. CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs.

    Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer

  51. BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics.

    Suresh Bishnoi, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan

  52. Training Graph Transformers via Curriculum-Enhanced Attention Distillation.

    Yisong Huang, Jin Li, Xinlong Chen, Yang-Geng Fu

  53. Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs.

    Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný

  54. GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking.

    Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj K. Singh, Sourav Medya, Sayan Ranu

  55. On the Stability of Expressive Positional Encodings for Graphs.

    Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li

  56. Understanding Expressivity of GNN in Rule Learning.

    Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao

  57. GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs.

    Pengcheng Jiang, Cao Xiao, Adam Cross, Jimeng Sun

  58. Deep Temporal Graph Clustering.

    Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu

  59. DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption.

    Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo

  60. Debiasing Attention Mechanism in Transformer without Demographics.

    Shenyu Lu, Yipei Wang, Xiaoqian Wang

  61. Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks.

    Shih-Hsin Wang, Yung-Chang Hsu, Justin M. Baker, Andrea L. Bertozzi, Jack Xin, Bao Wang

  62. Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials.

    Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram S. Deshpande

  63. Locality-Aware Graph Rewiring in GNNs.

    Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni

  64. Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.

    Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

  65. Mixture of Weak and Strong Experts on Graphs.

    Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo

  66. Talk like a Graph: Encoding Graphs for Large Language Models.

    Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

  67. VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition.

    Chenyu Liu, Xinliang Zhou, Zhengri Zhu, Liming Zhai, Ziyu Jia, Yang Liu

  68. From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module.

    Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo

  69. Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks.

    Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo

  70. A Topological Perspective on Demystifying GNN-Based Link Prediction Performance.

    Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr

  71. Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space.

    Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan

  72. Orbit-Equivariant Graph Neural Networks.

    Matthew Morris, Bernardo Cuenca Grau, Ian Horrocks

  73. Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning.

    Finn Rietz, Erik Schaffernicht, Stefan Heinrich, Johannes A. Stork

  74. StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning.

    Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang

  75. On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters.

    Matthias Lanzinger, Pablo Barceló

  76. Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach.

    Christian Fabian, Kai Cui, Heinz Koeppl

  77. Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning.

    Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, Shirui Pan

  78. Scalable and Effective Implicit Graph Neural Networks on Large Graphs.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao

  79. Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks.

    Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

  80. Temporal Generalization Estimation in Evolving Graphs.

    Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang, Yunqiang Zhu, Chenghu Zhou, Shiyu Liang

  81. Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective.

    Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng, Xiang Ao

  82. Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors.

    Hang Yin, Zihao Wang, Yangqiu Song

  83. From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction.

    Yanbang Wang, Jon M. Kleinberg

  84. Graph Generation with K2-trees.

    Yunhui Jang, Dongwoo Kim, Sungsoo Ahn

  85. Adaptive Self-training Framework for Fine-grained Scene Graph Generation.

    Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park

  86. Towards Foundation Models for Knowledge Graph Reasoning.

    Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu

  87. GOAt: Explaining Graph Neural Networks via Graph Output Attribution.

    Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu, Di Niu

  88. Latent 3D Graph Diffusion.

    Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen

  89. Efficient and Scalable Graph Generation through Iterative Local Expansion.

    Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer

  90. Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel.

    Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

  91. Conformal Inductive Graph Neural Networks.

    Soroush H. Zargarbashi, Aleksandar Bojchevski

  92. Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs.

    Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han

  93. A Simple and Scalable Representation for Graph Generation.

    Yunhui Jang, Seul Lee, Sungsoo Ahn

  94. Hypergraph Dynamic System.

    Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao

  95. HoloNets: Spectral Convolutions do extend to Directed Graphs.

    Christian Koke, Daniel Cremers

  96. Learning Multi-Agent Communication from Graph Modeling Perspective.

    Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao

  97. Adversarial Attacks on Fairness of Graph Neural Networks.

    Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li

  98. Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection.

    Xiangyu Dong, Xingyi Zhang, Sibo Wang

  99. Polynormer: Polynomial-Expressive Graph Transformer in Linear Time.

    Chenhui Deng, Zichao Yue, Zhiru Zhang

  100. PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks.

    Junwei Su, Difan Zou, Chuan Wu

  101. A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks.

    Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen

  102. General Graph Random Features.

    Isaac Reid, Krzysztof Marcin Choromanski, Eli Berger, Adrian Weller

  103. Label-free Node Classification on Graphs with Large Language Models (LLMs).

    Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang

  104. M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering.

    Jiaxin Lu, Zetian Jiang, Tianzhe Wang, Junchi Yan

  105. Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph.

    Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel M. Ni, Heung-Yeung Shum, Jian Guo

  106. Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View.

    Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu

  107. iGraphMix: Input Graph Mixup Method for Node Classification.

    Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim, Kim Jin Seon

  108. Local Graph Clustering with Noisy Labels.

    Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang

  109. GraphPulse: Topological representations for temporal graph property prediction.

    Kiarash Shamsi, Farimah Poursafaei, Shenyang Huang, Tran Gia Bao Ngo, Baris Coskunuzer, Cuneyt Gurcan Akcora

  110. Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values.

    Xiaodan Chen, Xiucheng Li, Bo Liu, Zhijun Li

  111. Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning.

    Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, Vaibhav Rajan

  112. Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach.

    Aoqi Zuo, Yiqing Li, Susan Wei, Mingming Gong

  113. Boosting Graph Anomaly Detection with Adaptive Message Passing.

    Jingyan Chen, Guanghui Zhu, Chunfeng Yuan, Yihua Huang

  114. EX-Graph: A Pioneering Dataset Bridging Ethereum and X.

    Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He

  115. HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs.

    Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin

  116. FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction.

    Yuxing Tian, Yiyan Qi, Fan Guo

  117. LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference.

    Yifan Feng, Yihe Luo, Shihui Ying, Yue Gao

  118. Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.

    Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

  119. Complete and Efficient Graph Transformers for Crystal Material Property Prediction.

    Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

  120. Delta-AI: Local objectives for amortized inference in sparse graphical models.

    Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio

  121. Rethinking Label Poisoning for GNNs: Pitfalls and Attacks.

    Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

  122. Graph-constrained diffusion for End-to-End Path Planning.

    Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye

  123. Contrastive Learning is Spectral Clustering on Similarity Graph.

    Zhiquan Tan, Yifan Zhang, Jingqin Yang, Yang Yuan

  124. Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries.

    Haitz Sáez de Ocáriz Borde, Anastasis Kratsios

  125. BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs.

    Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai

  126. Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models.

    Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang

  127. Graph Lottery Ticket Automated.

    Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang

  128. InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes.

    Jiawei Sun, Kailai Li, Ruoxin Chen, Jie Li, Chentao Wu, Yue Ding, Junchi Yan

  129. Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions.

    Xiu-Chuan Li, Kun Zhang, Tongliang Liu

  130. VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs.

    Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec

  131. Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks.

    Federico Errica, Mathias Niepert

  132. Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs.

    Xiong Zhou, Xianming Liu, Feilong Zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji

  133. Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data.

    Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji

  134. Robust Angular Synchronization via Directed Graph Neural Networks.

    Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu

WSDM-2024

  1. LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection.

    Zijian Cai, Zhaoxuan Tan, Zhenyu Lei, Zifeng Zhu, Hongrui Wang, Qinghua Zheng, Minnan Luo

  2. Overlapping and Robust Edge-Colored Clustering in Hypergraphs.

    Alex Crane, Brian Lavallee, Blair D. Sullivan, Nate Veldt

  3. DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting.

    Tianyu Fu, Chiyue Wei, Yu Wang, Rex Ying

  4. User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation.

    Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan

  5. Incomplete Graph Learning via Attribute-Structure Decoupled Variational Auto-Encoder.

    Xinke Jiang, Zidi Qin, Jiarong Xu, Xiang Ao

  6. DiffKG: Knowledge Graph Diffusion Model for Recommendation.

    Yangqin Jiang, Yuhao Yang, Lianghao Xia, Chao Huang

  7. MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation.

    Yungi Kim, Taeri Kim, Won-Yong Shin, Sang-Wook Kim

  8. Text-Video Retrieval via Multi-Modal Hypergraph Networks.

    Qian Li, Lixin Su, Jiashu Zhao, Long Xia, Hengyi Cai, Suqi Cheng, Hengzhu Tang, Junfeng Wang, Dawei Yin

  9. Global Heterogeneous Graph and Target Interest Denoising for Multi-behavior Sequential Recommendation.

    Xuewei Li, Hongwei Chen, Jian Yu, Mankun Zhao, Tianyi Xu, Wenbin Zhang, Mei Yu

  10. Capturing Temporal Node Evolution via Self-supervised Learning: A New Perspective on Dynamic Graph Learning.

    Lingwen Liu, Guangqi Wen, Peng Cao, Jinzhu Yang, Weiping Li, Osmar R. Zaïane

  11. Knowledge Graph Context-Enhanced Diversified Recommendation.

    Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu

  12. Generative Models for Complex Logical Reasoning over Knowledge Graphs.

    Yu Liu, Yanan Cao, Shi Wang, Qingyue Wang, Guanqun Bi

  13. MADM: A Model-agnostic Denoising Module for Graph-based Social Recommendation.

    Wenze Ma, Yuexian Wang, Yanmin Zhu, Zhaobo Wang, Mengyuan Jing, Xuhao Zhao, Jiadi Yu, Feilong Tang

  14. Source Free Graph Unsupervised Domain Adaptation.

    Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang

  15. GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction.

    Amit Roy, Juan Shu, Jia Li, Carl Yang, Olivier Elshocht, Jeroen Smeets, Pan Li

  16. ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees.

    Sina Sajadmanesh, Daniel Gatica-Perez

  17. Rethinking and Simplifying Bootstrapped Graph Latents.

    Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng

  18. Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function.

    Binghui Wang, Minhua Lin, Tianxiang Zhou, Pan Zhou, Ang Li, Meng Pang, Hai Helen Li, Yiran Chen

  19. Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels.

    Fali Wang, Tianxiang Zhao, Suhang Wang

  20. LLMRec: Large Language Models with Graph Augmentation for Recommendation.

    Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang

  21. Towards Alignment-Uniformity Aware Representation in Graph Contrastive Learning.

    Rong Yan, Peng Bao, Xiao Zhang, Zhongyi Liu, Hui Liu

  22. Unified Pretraining for Recommendation via Task Hypergraphs.

    Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

  23. PhoGAD: Graph-based Anomaly Behavior Detection with Persistent Homology Optimization.

    Ziqi Yuan, Haoyi Zhou, Tianyu Chen, Jianxin Li

  24. RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis.

    Xusheng Zhao, Hao Peng, Qiong Dai, Xu Bai, Huailiang Peng, Yanbing Liu, Qinglang Guo, Philip S. Yu

  25. Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices.

    Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra

  26. The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation.

    Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng

  27. Dance with Labels: Dual-Heterogeneous Label Graph Interaction for Multi-intent Spoken Language Understanding.

    Zhihong Zhu, Xuxin Cheng, Hongxiang Li, Yaowei Li, Yuexian Zou

  28. WordGraph: A Python Package for Reconstructing Interactive Causal Graphical Models from Text Data.

    Amine Ferdjaoui, Séverine Affeldt, Mohamed Nadif

  29. Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform.

    Blaine Hill, Lihui Liu, Hanghang Tong

  30. An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis.

    Xuexiong Luo, Guangwei Dong, Jia Wu, Amin Beheshti, Jian Yang, Shan Xue

  31. Temporal Graph Analysis with TGX.

    Razieh Shirzadkhani, Shenyang Huang, Elahe Kooshafar, Reihaneh Rabbany, Farimah Poursafaei

  32. Bridging Text Data and Graph Data: Towards Semantics and Structure-aware Knowledge Discovery.

    Bowen Jin, Yu Zhang, Sha Li, Jiawei Han

  33. Gaussian Graphical Model-Based Clustering of Time Series Data.

    Kohei Obata

  34. Applications of LLMs in E-Commerce Search and Product Knowledge Graph: The DoorDash Case Study.

    Sudeep Das, Raghav Saboo, Chaitanya S. K. Vadrevu, Bruce Wang, Steven Xu

  35. Integrating Knowledge Graph Data with Large Language Models for Explainable Inference.

    Carlos Efrain Quintero Narvaez, Raúl Monroy

  36. The 5th International Workshop on Machine Learning on Graphs (MLoG).

    Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed

WWW-2024

  1. MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning

    Yun Zhu, Haizhou Shi, Zhenshuo Zhang, Siliang Tang

  2. Cost-effective Data Labelling for Graph Neural Networks

    Shixun Huang, Ge Lee, Zhifeng Bao, Shirui Pan

  3. Towards Expansive and Adaptive Hard Negative Mining: Graph Contrastive Learning via Subspace Preserving

    Zhezheng Hao, Haonan Xin, Wei Long, Liaoyuan Tang, Rong Wang, Feiping Nie

  4. FusionRender: Harnessing WebGPU's Power for Enhanced Graphics Performance on Web Browsers

    Weichen Bi, Yun Ma, Yudong Han, Yifan Chen, Deyu Tian, Jiaqi Du

  5. Dynamic Graph Information Bottleneck

    Haonan Yuan, Qingyun Sun, Xingcheng Fu, Cheng Ji, Jianxin Li

  6. Poisoning Attack on Federated Knowledge Graph Embedding

    Enyuan Zhou, Song Guo, Zhixiu Ma, Zicong Hong, Tao GUO, Peiran Dong

  7. Cooperative Classification and Rationalization for Graph Generalization

    Linan Yue, Qi Liu, Ye Liu, Weibo Gao, Fangzhou Yao, Wenfeng Li

  8. Temporal Conformity-aware Hawkes Graph Network for Recommendations

    Chenglong Ma, Yongli Ren, Pablo Castells, Mark Sanderson

  9. IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion

    Jiapu Wang, zheng cui, Boyue Wang, Shirui Pan, Junbin Gao, Baocai Yin, Wen Gao

  10. Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks

    Hao Liu, Jiarui Feng, Lecheng Kong, Dacheng Tao, Yixin Chen, Muhan Zhang

  11. Hierarchical Graph Signal Processing for Collaborative Filtering

    Jiafeng Xia, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu

  12. Masked Graph Autoencoder with Non-discrete Bandwidths

    Ziwen Zhao, Yuhua Li, Yixiong Zou, Jiliang Tang, Ruixuan Li

  13. Hierarchical Position Embedding of Graphs with Landmarks and Clustering for Link Prediction

    Minsang Kim, Seung Jun Baek

  14. λGrapher: A Resource-Efficient Serverless System for GNN Serving through Graph Sharing

    Haichuan Hu, Fangming Liu, Qiangyu Pei, Yongjie Yuan, Zichen Xu, Lin Wang

  15. Memory Disagreement: A Pseudo-Labeling Measure from Training Dynamics for Semi-supervised Graph Learning

    Hongbin Pei, Yuheng Xiong, Pinghui Wang, Jing Tao, Jialun Liu, Huiqi Deng, Jie Ma, Xiaohong Guan

  16. Collaborative Metapath Enhanced Corporate Default Risk Assessment on Heterogeneous Graph

    Zheng Zhang, yingsheng Ji, Jiachen Shen, Yushu Chen, Xi Zhang, Guangwen Yang

  17. Graph Contrastive Learning with Kernel Dependence Maximization for Social Recommendation

    Xuelian Ni, Fei Xiong, Yu Zheng, Liang Wang

  18. Extracting Small Subgraphs in Road Networks

    Sara Ahmadian, Sreenivas Gollapudi, Gregory M Hutchins, Kostas Kollias, Xizhi Tan

  19. Game-theoretic Counterfactual Explanation for Graph Neural Networks

    Chirag P Chhablani, Sarthak Jain, Akshay Channesh, Ian A. Kash, Sourav Medya

  20. MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs

    Xingtong Yu, chang zhou, Yuan Fang, Xinming Zhang

  21. ReliK: A Reliability Measure for Knowledge Graph Embeddings

    Maximilian K Egger, Wenyue Ma, Davide Mottin, Panagiotis Karras, Ilaria Bordino, Francesco Gullo, Aris Anagnostopoulos

  22. TATKC: A Temporal Graph Neural Network for Fast Approximate Temporal Katz Centrality Ranking

    Tianming Zhang, Junkai Fang, Zhengyi Yang, Bin Cao, JING FAN

  23. GRASP: Hardening Serverless Applications through Graph Reachability Analysis of Security Policies

    Isaac Polinsky, Pubali Datta, Adam Bates, William Enck

  24. Efficient Exact and Approximate Betweenness Centrality Computation for Temporal Graphs

    Tianming Zhang, Yunjun Gao, jie zhao, Lu Chen, Lu Jin, Zhengyi Yang, Bin Cao, JING FAN

  25. GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning

    Yun Zhu, Yaoke Wang, Haizhou Shi, Zhenshuo Zhang, Dian Jiao, Siliang Tang

  26. SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding

    Ruiyi Yang, Flora Salim, Hao Xue

  27. Rethinking Node-wise Propagation for Large-scale Graph Learning

    Xunkai Li, Jingyuan Ma, Zhengyu Wu, Daohan Su, Zhang wen tao, Rong-Hua Li, Guoren Wang

  28. Fact Embedding through Diffusion Model for Knowledge Graph Completion

    xiao Long, Liansheng Zhuang, Aodi Li, Houqiang Li, Shafei Wang

  29. Graph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph

    Linfeng Cao, Haoran Deng, Yang Yang, Chunping Wang, Lei CHEN

  30. GAUSS: GrAph-customized Universal Self-Supervised Learning

    Liang Yang, Wei Xiao Hu, Jizhong Xu, Runjie Shi, Dongxiao He, Chuan Wang, Xiaochun Cao, Zhen Wang, bingxin niu, Yuanfang Guo

  31. VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation

    Geon Lee, Soo Yong Lee, Kijung Shin

  32. Divide, Conquer, and Coalesce: Meta Parallel Graph Neural Network for IoT Intrusion Detection at Scale

    Hua Ding, Lixing Chen, Shenghong Li, Yang Bai, Pan Zhou, Zhe Qu

  33. SMUG: Sand Mixing for Unobserved Class Detection in Graph Few-Shot Learning

    Chenxu Wang, Xichan Nie, Jinfeng Chen, Pinghui Wang, Junzhou Zhao, Xiaohong Guan

  34. Graph Contrastive Learning with Cohesive Subgraph Awareness

    Yucheng Wu, Leye Wang, Xiao Han, Han-Jia Ye

  35. Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection

    Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang

  36. Graph Contrastive Learning Reimagined: Exploring Universality

    Jiaming Zhuo, can cui, kun fu, bingxin niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang

  37. Linear-Time Graph Neural Networks for Scalable Recommendations

    Jiahao Zhang, Rui Xue, Wenqi Fan, Xu Xin, Qing Li, Jian Pei, Xiaorui Liu

  38. GNNFingers: A Fingerprinting Framework for Verifying Ownerships of Graph Neural Networks

    Xiaoyu You, Youhe Jiang, Jianwei Xu, Mi Zhang, Min Yang

  39. A Method for Assessing Inference Patterns Captured by Embedding Models in Knowledge Graphs

    Narayanan Asuri Krishnan, Carlos Rivero

  40. Using Model Calibration to Evaluate Link Prediction in Knowledge Graphs

    Aishwarya Rao, Narayanan Asuri Krishnan, Carlos Rivero

  41. Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation

    Zhen Zhang, Meihan Liu, an hui wang, Hongyang Chen, Zhao Li, Jiajun Bu, Bingsheng He

  42. Graph Fairness Learning under Distribution Shifts

    yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi

  43. Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials

    Mingguo He, Zhewei Wei, shikun feng, Zhengjie Huang, Weibin Li, Yu Sun, dianhai yu

  44. PACER: Network Embedding From Positional to Structural

    Yuchen Yan, Hu Yongyi, Qinghai Zhou, Lihui Liu, Zhichen Zeng, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hanghang Tong

  45. Macro Graph Neural Networks for Online Billion-Scale Recommender Systems

    Hao Chen, Yuanchen Bei, Qijie Shen, Yue Xu, Sheng Zhou, Wenbing Huang, Feiran Huang, Senzhang Wang, Xiao Huang

  46. Self-Guided Robust Graph Structure Refinement

    Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park

  47. DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy

    Qiuchen Zhang, Hong kyu Lee, Jing Ma, Jian Lou, Carl Yang, Li Xiong

  48. Fair Graph Representation Learning via Sensitive Attribute Disentanglement

    Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen

  49. MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification

    Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen

  50. GraphPro: Graph Pretraining and Prompt Learning for Recommendation

    Yuhao Yang, Lianghao Xia, Da Luo, konyellin, Chao Huang

  51. Invariant Graph Learning for Causal Effect Estimation

    Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, JUN ZHOU, Xiang Wang

  52. EXGC: Bridging Efficiency and Explainability in Graph Condensation

    Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

  53. Identifying VPN Servers through Graph-Represented Behaviors

    chenxu wang, Jiangyi Yin, Zhao Li, Hongbo Xu, Zhongyi Zhang, Qingyun Liu

  54. DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning

    Seungyoon Choi, Wonjoong Kim, Sungwon Kim, Yeonjun In, Sein Kim, Chanyoung Park

  55. Calibrating Graph Neural Networks from a Data-centric Perspective

    Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, JUN ZHOU

  56. Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern Retrieval

    Wentao Ding, Jinmao Li, Liangchuan Luo, Yuzhong Qu

  57. HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding

    Honggen Zhang, June Zhang, Igor Molybog

  58. Bridging the Space Gap: Unifying Geometry Knowledge Graph Embedding with Optimal Transport

    Yuhan Liu, Zelin Cao, Gao Xing, Ji Zhang, Rui Yan

  59. Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs

    Yuhan Wu, Yuanyuan Xu, Wenjie Zhang, Xiwei Xu, Ying Zhang

  60. Graph Principal Flow Network for Conditional Graph Generation

    Zhanfeng Mo, Tianze Luo, Sinno Pan

  61. Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs

    Zhen WANG, Yaliang Li, Bolin Ding, Yule Li, Zhewei Wei

  62. Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search

    Songhao Wu, quan Tu, Hong Liu, Xu Jia, Zhongyi Liu, Guannan Zhang, Ran Lucien Wang, Xiuying Chen, Rui Yan

  63. Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning

    Shuyao Wang, Yongduo Sui, Chao Wang, Hui Xiong

  64. Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem

    Chen Huang, Haoyang Li, Yifan Zhang, Wenqiang Lei, Jiancheng Lv

  65. A Quasi-Wasserstein Loss for Learning Graph Neural Networks

    Minjie Cheng, Hongteng Xu

  66. A Simple but Effective Approach for Unsupervised Few-Shot Graph Classification

    Yonghao Liu, Lan Huang, Bowen Cao, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan

  67. UniLP: Unified Topology-aware Generative Framework for Link Prediction in Knowledge Graph

    Ben Liu, Miao Peng, Wenjie Xu, Xu Jia, Min Peng

  68. ARTEMIS: Detecting Airdrop Hunters in NFT Markets with a Graph Learning System

    Chenyu Zhou, Hongzhou Chen, Wu Hao, Junyu Zhang, Wei Cai

  69. Distributionally Robust Graph-based Recommendation System

    Bohao Wang, Jiawei Chen, Changdong Li, Sheng Zhou, Qihao Shi, Yang Gao, Yan Feng, Chun Chen, Can Wang

  70. GNNShap: Scalable and Accurate GNN Explanation using Shapley Values

    Selahattin Akkas, Ariful Azad

  71. Decoupled Variational Graph Autoencoder for Link Prediction

    Yoon-Sik Cho

  72. Graph Out-of-Distribution Generalization via Causal Intervention

    Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan

  73. Diagrammatic Reasoning for ALC Visualization with Logic Graphs

    Ildar Baimuratov

  74. Adversarial Mask Explainer for Graph Neural Networks

    Wei Zhang, XIAOFAN LI, Wolfgang Nejdl

  75. High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text Attributed Graphs

    Peiyan Zhang, Chaozhuo Li, Liying Kang, Feiran Huang, Senzhang Wang, Xin Xie, Sunghun Kim

  76. Unifying Local and Global Knowledge: Empowering Large Language Models as Political Experts with Knowledge Graphs

    Xinyi Mou, Zejun Li, Hanjia Lyu, Jiebo Luo, zhongyu wei

  77. Inductive Graph Alignment Prompt: Bridging the Gap between Graph Pre-training and Inductive Fine-tuning From Spectral Perspective

    Yuchen Yan, Peiyan Zhang, Zheng Fang, QingqingLong

  78. On the Feasibility of Simple Transformer for Dynamic Graph Modeling

    Yuxia Wu, Yuan Fang, Lizi Liao

  79. Densest Subhypergraph: Negative Supermodular Functions and Strongly Localized Methods

    Yufan Huang, David F. Gleich, Nate Veldt

  80. Can GNN be Good Adapter for LLMs?

    Xuanwen Huang, Kaiqiao Han, Yang Yang, Dezheng Bao, Quanjin Tao, Ziwei Chai, Qi Zhu

  81. When Imbalance Meets Imbalance: Structure-driven Learning for Imbalanced Graph Classification

    Wei Xu, Pengkun Wang, Zhe Zhao, Binwu Wang, Xu Wang, Yang Wang

  82. Disambiguated Node Classification with Graph Neural Networks

    Tianxiang Zhao, Xiang Zhang, Suhang Wang

  83. Finding Densest Subgraphs with Edge-Color Constraints

    Lutz Oettershagen, Honglian Wang, Aristides Gionis

  84. Diffusion-based Negative Sampling on Graphs for Link Prediction

    Trung-Kien Nguyen, Yuan Fang

  85. Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss

    David Kang, Qiaozhu Mei, Sang-Wook Kim

  86. GAMMA: Graph Neural Network-Based Multi-Bottleneck Localization for Microservices Applications

    Gagan Somashekar, Anurag Dutt, Mainak Adak, Tania Lorido Botran, Anshul Gandhi

  87. General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout

    AN ZHANG, Wenchang Ma, Pengbo Wei, Leheng Sheng, Xiang Wang

  88. Graph Anomaly Detection with Bi-level Optimization

    Yuan Gao, Junfeng Fang, Yongduo Sui, Yangyang Li, Xiang Wang, HuaMin Feng, Yongdong Zhang

  89. Globally Interpretable Graph Learning via Distribution Matching

    Yi Nian, Yurui Chang, Wei Jin, Lu Lin

  90. Benchmark and Neural Architecture for Conversational Entity Retrieval from a Knowledge Graph

    Mona Zamiri, Yao Qiang, Fedor Nikolaev, Dongxiao Zhu, Alexander Kotov

  91. Heterogeneous Subgraph Transformer for Fake News Detection

    Yuchen Zhang, Xiaoxiao Ma, Jia Wu, Jian Yang, Hao Fan

  92. GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks

    Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi

  93. HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks

    Yihong Ma, Ning Yan, Jiayu Li, Masood S. Mortazavi, Nitesh Chawla

  94. Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs via Active Learning

    Weijian Yu, Jie Yang, Dingqi Yang

  95. Graph Contrastive Learning via Interventional View Generation

    Zengyi Wo, Minglai Shao, Wenjun Wang, Xuan Guo, Lu Lin

  96. DenseFlow: Spotting Cryptocurrency Money Laundering in Ethereum Transaction Graphs

    Dan Lin, Jiajing Wu, Yunmei Yu, Qishuang Fu, Zibin Zheng, Changlin Yang

  97. Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation

    Bo Yan, YANG CAO, Haoyu Wang, Wenchuan Yang, Junping Du, Chuan Shi

  98. Fast Graph Condensation with Structure-based Neural Tangent Kernel

    Lin WANG, Wenqi Fan, Jiatong LI, Yao Ma, Qing Li

  99. Endowing Pre-trained Graph Models with Provable Fairness

    Zhang Zhong Jian, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi

  100. Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach

    Keke Huang, Wencai Cao, Hoang Ta, Xiaokui Xiao, Pietro Lio

  101. Friend or Foe? Mining Suspicious Behavior via Graph Capsule Infomax Detector against Fraudsters

    Xiangping Zheng, Bo Wu, Xun Liang, Wei Li

  102. Full-Attention Driven Graph Contrastive Learning: With Effective Mutual Information Insight

    Long Li, Zemin Liu, Chenghao Liu, Jianling Sun

  103. Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets

    Xuhui Jiang, Chengjin Xu, Yinghan Shen, Yuanzhuo Wang, Fenglong Su, Zhichao Shi, Fei Sun, Zixuan Li, Jian Guo, Huawei Shen

ICDE-2024

  1. Enabling Roll-Up and Drill-Down Operations in News Exploration with Knowledge Graphs for Due Diligence and Risk Management.

    Sha Wang, Yuchen Li, Hanhua Xiao, Zhifeng Bao, Lambert Deng, Yanfei Dong

  2. Bipartite Graph Analytics: Current Techniques and Future Trends.

    Hanchen Wang, Kai Wang, Wenjie Zhang, Ying Zhang

  3. Knowledge Graph Enhanced Multimodal Transformer for Image-Text Retrieval.

    Juncheng Zheng, Meiyu Liang, Yang Yu, Yawen Li, Zhe Xue

  4. Graph Contrastive Learning for Truth Inference.

    Hao Liu, Jiacheng Liu, Feilong Tang, Peng Li, Long Chen, Jiadi Yu, Yanmin Zhu, Min Gao, Yanqin Yang, Xiaofeng Hou

  5. Efficient Example-Guided Interactive Graph Search.

    Zhuowei Zhao, Junhao Gan, Jianzhong Qi, Zhifeng Bao

  6. Ontology-Mediated Query Answering Using Graph Patterns with Conditions.

    Ping Lu, Ting Deng, Haoyuan Zhang, Yufeng Jin, Feiyi Liu, Tiancheng Mao, Lexiao Liu

  7. Personalized PageRanks over Dynamic Graphs - The Case for Optimizing Quality of Service.

    Zulun Zhu, Siqiang Luo, Wenqing Lin, Sibo Wang, Dingheng Mo, Chunbo Li

  8. Structure- and Logic-Aware Heterogeneous Graph Learning for Recommendation.

    Anchen Li, Bo Yang, Huan Huo, Farookh Khadeer Hussain, Guandong Xu

  9. Graph Augmentation for Recommendation.

    Qianru Zhang, Lianghao Xia, Xuheng Cai, Siu-Ming Yiu, Chao Huang, Christian S. Jensen

  10. Meta-optimized Structural and Semantic Contrastive Learning for Graph Collaborative Filtering.

    Yongjing Hao, Pengpeng Zhao, Jianfeng Qu, Lei Zhao, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou

  11. Multi-Modal Siamese Network for Few-Shot Knowledge Graph Completion.

    Yuyang Wei, Wei Chen, Xiaofang Zhang, Pengpeng Zhao, Jianfeng Qu, Lei Zhao

  12. Local-Global History-Aware Contrastive Learning for Temporal Knowledge Graph Reasoning.

    Wei Chen, Huaiyu Wan, Yuting Wu, Shuyuan Zhao, Jiayaqi Cheng, Yuxin Li, Youfang Lin

  13. E2GCL: Efficient and Expressive Contrastive Learning on Graph Neural Networks.

    Haoyang Li, Shimin Di, Lei Chen, Xiaofang Zhou

  14. KGLink: A Column Type Annotation Method that Combines Knowledge Graph and Pre-Trained Language Model.

    Yubo Wang, Hao Xin, Lei Chen

  15. GradGCL: Gradient Graph Contrastive Learning.

    Ran Li, Shimin Di, Lei Chen, Xiaofang Zhou

  16. CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks.

    Yuanchen Bei, Hao Xu, Sheng Zhou, Huixuan Chi, Haishuai Wang, Mengdi Zhang, Zhao Li, Jiajun Bu

  17. Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach.

    Xing Ai, Jialong Zhou, Yulin Zhu, Gaolei Li, Tomasz P. Michalak, Xiapu Luo, Kai Zhou

  18. SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting.

    Yue Jiang, Xiucheng Li, Yile Chen, Shuai Liu, Weilong Kong, Antonis F. Lentzakis, Gao Cong

  19. Knowledge-Enhanced Recommendation with User-Centric Subgraph Network.

    Guangyi Liu, Quanming Yao, Yongqi Zhang, Lei Chen

  20. Model Selection with Model Zoo via Graph Learning.

    Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla, Alessandro Bozzon, Rihan Hai

  21. Across Images and Graphs for Question Answering.

    Zhenyu Wen, Jiaxu Qian, Bin Qian, Qin Yuan, Jianbin Qin, Qi Xuan, Ye Yuan

  22. Differentially Private Graph Neural Networks for Link Prediction.

    Xun Ran, Qingqing Ye, Haibo Hu, Xin Huang, Jianliang Xu, Jie Fu

  23. Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks.

    He Zhang, Xingliang Yuan, Shirui Pan

  24. Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling.

    Hussein Abdallah, Waleed Afandi, Panos Kalnis, Essam Mansour

  25. Authenticated Keyword Search on Large-Scale Graphs in Hybrid-Storage Blockchains.

    Siyu Li, Zhiwei Zhang, Jiang Xiao, Meihui Zhang, Ye Yuan, Guoren Wang

  26. Authenticated Subgraph Matching in Hybrid-Storage Blockchains.

    Siyu Li, Zhiwei Zhang, Meihui Zhang, Ye Yuan, Guoren Wang

  27. Graph Computation with Adaptive Granularity.

    Ruiqi Xu, Yue Wang, Xiaokui Xiao

  28. Why-Not Explainable Graph Recommender.

    Hervé-Madelein Attolou, Katerina Tzompanaki, Kostas Stefanidis, Dimitris Kotzinos

  29. GAGE: Genetic Algorithm-Based Graph Explainer for Malware Analysis.

    Mohd Saqib, Benjamin C. M. Fung, Philippe Charland, Andrew Walenstein

  30. Fairgen: Towards Fair Graph Generation.

    Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He

  31. Butterfly Counting over Bipartite Graphs with Local Differential Privacy.

    Yizhang He, Kai Wang, Wenjie Zhang, Xuemin Lin, Wei Ni, Ying Zhang

  32. Temporal Graph Generation Featuring Time-Bound Communities.

    Shuwen Zheng, Chaokun Wang, Cheng Wu, Yunkai Lou, Hao Feng, Xuran Yang

  33. Accelerating SpMV for Scale-Free Graphs with Optimized Bins.

    YuAng Chen, Jeffrey Xu Yu

  34. PlatoD2GL: An Efficient Dynamic Deep Graph Learning System for Graph Neural Network Training on Billion-Scale Graphs.

    Xing Huang, Dandan Lin, Weiyi Huang, Shijie Sun, Jie Wen, Chuan Chen

  35. Fast Iterative Graph Computing with Updated Neighbor States.

    Yijie Zhou, Shufeng Gong, Feng Yao, Hanzhang Chen, Song Yu, Pengxi Liu, Yanfeng Zhang, Ge Yu, Jeffrey Xu Yu

  36. GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy.

    Tianhao Peng, Wenjun Wu, Haitao Yuan, Zhifeng Bao, Zhao Pengrui, Xin Yu, Xuetao Lin, Yu Liang, Yanjun Pu

  37. Querying Historical Cohesive Subgraphs Over Temporal Bipartite Graphs.

    Shunyang Li, Kai Wang, Xuemin Lin, Wenjie Zhang, Yizhang He, Long Yuan

  38. Positive Communities on Signed Graphs That Are Not Echo Chambers: A Clique-Based Approach.

    Alexander Zhou, Yue Wang, Lei Chen, M. Tamer Özsu

  39. Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs.

    Long Yuan, Kongzhang Hao, Xuemin Lin, Wenjie Zhang

  40. Masked Graph Modeling with Multi- View Contrast.

    Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, Xiang Wang

  41. GShop: Towards Flexible Pricing for Graph Statistics.

    Chen Chen, Ye Yuan, Zhenyu Wen, Yu-Ping Wang, Guoren Wang

  42. LearnSC: An Efficient and Unified Learning-Based Framework for Subgraph Counting Problem.

    Wenzhe Hou, Xiang Zhao, Bo Tang

  43. Reducing Resource Usage for Continuous Model Updating and Predictive Query Answering in Graph Streams.

    Qu Liu, Adam King, Tingjian Ge

  44. Graph Anomaly Detection with Domain-Agnostic Pre-Training and Few-Shot Adaptation.

    Xujia Li, Lei Chen

  45. NC-ALG: Graph-Based Active Learning Under Noisy Crowd.

    Wentao Zhang, Yexin Wang, Zhenbang You, Yang Li, Gang Cao, Zhi Yang, Bin Cui

  46. CINA: Curvature-Based Integrated Network Alignment with Hypergraph.

    Pengfei Jiao, Yuanqi Liu, Yinghui Wang, Ge Zhang

  47. Scalable Community Search with Accuracy Guarantee on Attributed Graphs.

    Yuxiang Wang, Shuzhan Ye, Xiaoliang Xu, Yuxia Geng, Zhenghe Zhao, Xiangyu Ke, Tianxing Wu

  48. Self-Training GNN-based Community Search in Large Attributed Heterogeneous Information Networks.

    Yuan Li, Xiuxu Chen, Yuhai Zhao, Wen Shan, Zhengkui Wang, Guoli Yang, Guoren Wang

  49. HGAMLP: Heterogeneous Graph Attention MLP with De-Redundancy Mechanism.

    Yuxuan Liang, Wentao Zhang, Zeang Sheng, Ling Yang, Jiawei Jiang, Yunhai Tong, Bin Cui

  50. FocusCore Decomposition of Multilayer Graphs.

    Run-An Wang, Dandan Liu, Zhaonian Zou

  51. Search to Fine-Tune Pre-Trained Graph Neural Networks for Graph-Level Tasks.

    Zhili Wang, Shimin Di, Lei Chen, Xiaofang Zhou

  52. BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection.

    Jie Liu, Mengting He, Xuequn Shang, Jieming Shi, Bin Cui, Hongzhi Yin

  53. Discovering Personalized Characteristic Communities in Attributed Graphs.

    Yudong Niu, Yuchen Li, Panagiotis Karras, Yanhao Wang, Zhao Li

  54. TP-GNN: Continuous Dynamic Graph Neural Network for Graph Classification.

    Jie Liu, Jiamou Liu, Kaiqi Zhao, Yanni Tang, Wu Chen

  55. GraphHI: Boosting Graph Neural Networks for Large-Scale Graphs.

    Hao Feng, Chaokun Wang, Ziyang Liu, Yunkai Lou, Zhenyu Liu, Xiaokun Zhu, Yongjun Bao, Weipeng Yan

  56. DiscoGNN: A Sample-Efficient Framework for Self-Supervised Graph Representation Learning.

    Jun Xia, Shaorong Chen, Yue Liu, Zhangyang Gao, Jiangbin Zheng, Xihong Yang, Stan Z. Li

  57. Incorporating Dynamic Temperature Estimation into Contrastive Learning on Graphs.

    Ziyang Liu, Chaokun Wang, Liqun Yang, Yunkai Lou, Hao Feng, Cheng Wu, Kai Zheng, Yang Song

  58. Newton Sketches: Estimating Node Intimacy in Dynamic Graphs Using Newton's Law of Cooling.

    Qizhi Chen, Ke Wang, Aoran Li, Yuhan Wu, Tong Yang, Bin Cui

  59. Counting Butterflies in Fully Dynamic Bipartite Graph Streams.

    Serafeim Papadias, Zoi Kaoudi, Varun Pandey, Jorge-Arnulfo Quiané-Ruiz, Volker Markl

  60. BIM: Improving Graph Neural Networks with Balanced Influence Maximization.

    Wentao Zhang, Xinyi Gao, Ling Yang, Meng Cao, Ping Huang, Jiulong Shan, Hongzhi Yin, Bin Cui

  61. SES: Bridging the Gap Between Explainability and Prediction of Graph Neural Networks.

    Zhenhua Huang, Kunhao Li, Shaojie Wang, Zhaohong Jia, Wentao Zhu, Sharad Mehrotra

  62. Efficient Cross-layer Community Search in Large Multilayer Graphs.

    Longxu Sun, Xin Huang, Zheng Wu, Jianliang Xu

  63. Large Subgraph Matching: A Comprehensive and Efficient Approach for Heterogeneous Graphs.

    Hongtai Cao, Qihao Wang, Xiaodong Li, Matin Najafi, Kevin Chen-Chuan Chang, Reynold Cheng

  64. Adaptive Hypergraph Network for Trust Prediction.

    Rongwei Xu, Guanfeng Liu, Yan Wang, Xuyun Zhang, Kai Zheng, Xiaofang Zhou

  65. Wings: Efficient Online Multiple Graph Pattern Matching.

    Guanxian Jiang, Yunjian Zhao, Yichao Li, Zhi Liu, Tatiana Jin, Wanying Zheng, Boyang Li, James Cheng

  66. SGCL: Semantic-aware Graph Contrastive Learning with Lipschitz Graph Augmentation.

    Jinhao Cui, Heyan Chai, Xu Yang, Ye Ding, Binxing Fang, Qing Liao

  67. Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation.

    Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin

  68. Graph Condensation for Inductive Node Representation Learning.

    Xinyi Gao, Tong Chen, Yilong Zang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, Hongzhi Yin

  69. Graphix: "One User's JSON is Another User's Graph".

    Glenn Galvizo, Michael J. Carey

  70. CSM-TopK: Continuous Subgraph Matching with TopK Density Constraints.

    Chuchu Gao, Youhuan Li, Zhibang Yang, Xu Zhou

  71. Denoising High-Order Graph Clustering.

    Yonghao Chen, Ruibing Chen, Qiaoyun Li, Xiaozhao Fang, Jiaxing Li, Wai Keung Wong

  72. A Revisit to Graph Neighborhood Cardinality Estimation.

    Pinghui Wang, Yuanming Zhang, Kuankuan Cheng, Junzhou Zhao

  73. Attributed Network Embedding in Streaming Style.

    Anbiao Wu, Ye Yuan, Changsheng Li, Yuliang Ma, Hao Zhang

  74. Faster Depth-First Subgraph Matching on GPUs.

    Lyuheng Yuan, Da Yan, Jiao Han, Akhlaque Ahmad, Yang Zhou, Zhe Jiang

  75. G2-AIMD: A Memory-Efficient Subgraph-Centric Framework for Efficient Subgraph Finding on GPUs.

    Lyuheng Yuan, Akhlaque Ahmad, Da Yan, Jiao Han, Saugat Adhikari, Xiaodong Yu, Yang Zhou

  76. Fine-Grained Anomaly Detection on Dynamic Graphs via Attention Alignment.

    Dong Chen, Xiang Zhao, Weidong Xiao

  77. GPU-Accelerated Batch-Dynamic Subgraph Matching.

    Linshan Qiu, Lu Chen, Hailiang Jie, Xiangyu Ke, Yunjun Gao, Yang Liu, Zetao Zhang

  78. I/O Efficient Max-Truss Computation in Large Static and Dynamic Graphs.

    Jiaqi Jiang, Qi Zhang, Rong-Hua Li, Qiangqiang Dai, Guoren Wang

  79. Efficient Multi-Query Oriented Continuous Subgraph Matching.

    Ziyi Ma, Jianye Yang, Xu Zhou, Guoqing Xiao, Jianhua Wang, Liang Yang, Kenli Li, Xuemin Lin

  80. Label Constrained Reachability Queries on Time Dependent Graphs.

    Yishu Wang, Jinlong Chu, Ye Yuan, Yu Gu, Hangxu Ji, Hao Zhang

  81. Time-Constrained Continuous Subgraph Matching Using Temporal Information for Filtering and Backtracking.

    Seunghwan Min, Jihoon Jang, Kunsoo Park, Dora Giammarresi, Giuseppe F. Italiano, Wook-Shin Han

  82. Adaptive Truss Maximization on Large Graphs: A Minimum Cut Approach.

    Zitan Sun, Xin Huang, Chengzhi Piao, Cheng Long, Jianliang Xu

  83. TimeSGN: Scalable and Effective Temporal Graph Neural Network.

    Yuanyuan Xu, Wenjie Zhang, Ying Zhang, Maria E. Orlowska, Xuemin Lin

  84. NewSP: A New Search Process for Continuous Subgraph Matching over Dynamic Graphs.

    Ziming Li, Youhuan Li, Xinhuan Chen, Lei Zou, Yang Li, Xiaofeng Yang, Hongbo Jiang

  85. Querying Cohesive Subgraph Regarding Span-Constrained Triangles on Temporal Graphs.

    Chuhan Hu, Ming Zhong, Yuanyuan Zhu, Tieyun Qian, Ting Yu, Hongyang Chen, Mengchi Liu, Jeffrey Xu Yu

  86. Generating Robust Counterfactual Witnesses for Graph Neural Networks.

    Dazhuo Qiu, Mengying Wang, Arijit Khan, Yinghui Wu

  87. Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning.

    Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang, Bo Du, Jiawei Jiang

  88. Representation Learning for Entity Alignment in Knowledge Graph: A Design Space Exploration.

    Peng Huang, Meihui Zhang, Ziyue Zhong, Chengliang Chai, Ju Fan

  89. Sylvie: 3D-Adaptive and Universal System for Large-Scale Graph Neural Network Training.

    Meng Zhang, Qinghao Hu, Cheng Wan, Haozhao Wang, Peng Sun, Yonggang Wen, Tianwei Zhang

  90. Benchtemp: A General Benchmark for Evaluating Temporal Graph Neural Networks.

    Qiang Huang, Xin Wang, Susie Xi Rao, Zhichao Han, Zitao Zhang, Yongjun He, Quanqing Xu, Yang Zhao, Zhigao Zheng, Jiawei Jiang

  91. Fast Query Answering by Labeling Index on Uncertain Graphs.

    Zeyu Wang, Qihao Shi, Jiawei Chen, Can Wang, Mingli Song, Xinyu Wang

  92. Resistance Eccentricity in Graphs: Distribution, Computation and Optimization.

    Zenan Lu, Xiaotian Zhou, Ahad N. Zehmakan, Zhongzhi Zhang

  93. IVE: Accelerating Enumeration-Based Subgraph Matching via Exploring Isolated Vertices.

    Zite Jiang, Shuai Zhang, Xingzhong Hou, Mengting Yuan, Haihang You

  94. CAGRA: Highly Parallel Graph Construction and Approximate Nearest Neighbor Search for GPUs.

    Hiroyuki Ootomo, Akira Naruse, Corey Nolet, Ray Wang, Tamas Feher, Yong Wang

  95. HJG: An Effective Hierarchical Joint Graph for ANNS in Multi-Metric Spaces.

    Yifan Zhu, Lu Chen, Yunjun Gao, Ruiyao Ma, Baihua Zheng, Jingwen Zhao

  96. Learning Time-Aware Graph Structures for Spatially Correlated Time Series Forecasting.

    Minbo Ma, Jilin Hu, Christian S. Jensen, Fei Teng, Peng Han, Zhiqiang Xu, Tianrui Li

  97. FRESH: Towards Efficient Graph Queries in an Outsourced Graph.

    Kai Huang, Yunqi Li, Qingqing Ye, Yao Tian, Xi Zhao, Yue Cui, Haibo Hu, Xiaofang Zhou

  98. Firzen: Firing Strict Cold-Start Items with Frozen Heterogeneous and Homogeneous Graphs for Recommendation.

    Hulingxiao He, Xiangteng He, Yuxin Peng, Zifei Shan, Xin Su

  99. Unsupervised Multimodal Graph Contrastive Semantic Anchor Space Dynamic Knowledge Distillation Network for Cross-Media Hash Retrieval.

    Yang Yu, Meiyu Liang, Mengran Yin, Kangkang Lu, Junping Du, Zhe Xue

  100. Routing-Guided Learned Product Quantization for Graph-Based Approximate Nearest Neighbor Search.

    Qiang Yue, Xiaoliang Xu, Yuxiang Wang, Yikun Tao, Xuliyuan Luo

  101. KartGPS: Knowledge Base Update with Temporal Graph Pattern-based Semantic Rules.

    Hao Xin, Lei Chen

  102. GaussDB-Global: A Geographically Distributed Database System.

    Puya Memarzia, Huaxin Zhang, Kelvin Ho, Ronen Grosman, Jiang Wang

  103. Comparing Personalized Relevance Algorithms for Directed Graphs.

    Luca Cavalcanti, Cristian Consonni, Martin Brugnara, David Laniado, Alberto Montresor

  104. FSM-Explorer: An Interactive Tool for Frequent Subgraph Pattern Mining From a Big Graph.

    Jalal Khalil, Da Yan, Lyuheng Yuan, Jiao Han, Saugat Adhikari, Cheng Long, Yang Zhou

  105. ChatGraph: Chat with Your Graphs.

    Yun Peng, Sen Lin, Qian Chen, Shaowei Wang, Lyu Xu, Xiaojun Ren, Yafei Li, Jianliang Xu

  106. KGSEC: A Modular Framework for Knowledge Graph Schema Extraction and Comparison.

    Petros Skoufis, Dimitrios Skoutas

  107. GraphLingo: Domain Knowledge Exploration by Synchronizing Knowledge Graphs and Large Language Models.

    Duy Le, Kris Zhao, Mengying Wang, Yinghui Wu

  108. Secure Normal Form: Mediation Among Cross Cryptographic Leakages in Encrypted Databases.

    Shufan Zhang, Xi He, Ashish Kundu, Sharad Mehrotra, Shantanu Sharma

  109. BIFROST: A Future Graph Database Runtime.

    James Clarkson, Georgios Theodorakis, Jim Webber

  110. PR-GNN: Enhancing PoC Report Recommendation with Graph Neural Network.

    Jiangtao Lu, Song Huang

  111. Construction and Enhancement of an RNA-Based Knowledge Graph for Discovering New RNA Drugs.

    Emanuele Cavalleri, Marco Mesiti

  112. Synergies Between Graph Data Management and Machine Learning in Graph Data Pipeline.

    Arijit Khan

  113. Observations and Opportunities in Solving Large-Scale Graph Data Processing Challenges at ByteDance by Using Heterogeneous Hardware.

    Cheng Chen, Shuai Zhang

  114. OOD-GNN: Out-of-Distribution Generalized Graph Neural Network: (Extended Abstract).

    Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu

  115. Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning (Extended Abstract).

    Ning Liu, Songlei Jian, Dongsheng Li, Yiming Zhang, Zhiquan Lai, Hongzuo Xu

  116. DKWS: A Distributed System for Keyword Search on Massive Graphs (Extended Abstract).

    Jiaxin Jiang, Byron Choi, Xin Huang, Jianliang Xu, Sourav S. Bhowmick

  117. Multi-Grained Semantics-Aware Graph Neural Networks (Extended abstract).

    Zhiqiang Zhong, Cheng-Te Li, Jun Pang

  118. Higher-Order Truss Decomposition in Graphs (Extended Abstract).

    Zi Chen, Long Yuan, Li Han, Zhengping Qian

  119. Finding the Maximum k- Balanced Biclique on Weighted Bipartite Graphs (Extended abstract).

    Yiwei Zhao, Zi Chen, Chen Chen, Xiaoyang Wang, Xuemin Lin, Wenjie Zhang

  120. Neural Similarity Search on Supergraph Containment (Extended Abstract).

    Hanchen Wang, Jianke Yu, Xiaoyang Wang, Chen Chen, Wenjie Zhang, Xuemin Lin

  121. Contrastive Graph Representations for Logical Formulas Embedding (Extended Abstract).

    Qika Lin, Jun Liu, Lingling Zhang, Yudai Pan, Xin Hu, Fangzhi Xu, Hongwei Zeng

  122. Incremental Graph Computation: Anchored Vertex Tracking in Dynamic Social Networks (Extended Abstract).

    Taotao Cai, Shuiqiao Yang, Jianxin Li, Quan Z. Sheng, Jian Yang, Xin Wang, Wei Emma Zhang, Longxiang Gao

  123. Searching Personalized k-wing in Bipartite Graphs (Extended Abstract).

    Aman Abidi, Lu Chen, Rui Zhou, Chengfei Liu

  124. Efficient Community Search in Edge-Attributed Graphs (Extended Abstract).

    Ling Li, Yuhai Zhao, Siqiang Luo, Guoren Wang, Zhengkui Wang

  125. Matching Knowledge Graphs in Entity Embedding Spaces: An Experimental Study [Extended Abstract].

    Weixin Zeng, Xiang Zhao, Zhen Tan, Jiuyang Tang, Xueqi Cheng

  126. Recommending Learning Objects through Attentive Heterogeneous Graph Convolution and Operation- Aware Neural Network (Extended Abstract).

    Yifan Zhu, Qika Lin, Hao Lu, Kaize Shi, Donglei Liu, James Chambua, Shanshan Wan, Zhendong Niu

  127. Inductive Link Prediction for Sequential-emerging Knowledge Graph.

    Yufeng Zhang, Wei Chen, Xi Chen, Qingzhi Ma, Lei Zhao

SIGMOD-2024

  1. BG3: A Cost Effective and I/O Efficient Graph Database in Bytedance.

    Wei Zhang, Cheng Chen, Qiange Wang, Wei Wang, Shijiao Yang, Bingyu Zhou, Huiming Zhu, Chao Chen, Yongjun Zhao, Yingqian Hu, Miaomiao Cheng, Meng Li, Hongfei Tan, Mengjin Liu, Hexiang Lin, Shuai Zhang, Lei Zhang

  2. PG-Triggers: Triggers for Property Graphs.

    Stefano Ceri, Anna Bernasconi, Alessia Gagliardi, Davide Martinenghi, Luigi Bellomarini, Davide Magnanimi

  3. GraphScope Flex: LEGO-like Graph Computing Stack.

    Tao He, Shuxian Hu, Longbin Lai, Dongze Li, Neng Li, Xue Li, Lexiao Liu, Xiaojian Luo, Bingqing Lyu, Ke Meng, Sijie Shen, Li Su, Lei Wang, Jingbo Xu, Wenyuan Yu, Weibin Zeng, Lei Zhang, Siyuan Zhang, Jingren Zhou, Xiaoli Zhou, Diwen Zhu

  4. NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention.

    Wentao Zhang, Guochen Yan, Yu Shen, Ling Yang, Yangyu Tao, Bin Cui, Jian Tang

  5. QueryShield: Cryptographically Secure Analytics in the Cloud.

    Ethan Seow, Yan Tong, Eli Baum, Sam Buxbaum, Muhammad Faisal, John Liagouris, Vasiliki Kalavri, Mayank Varia

  6. SIERRA: A Counterfactual Thinking-based Visual Interface for Property Graph Query Construction.

    Jiebing Ma, Sourav S. Bhowmick, Lester Tay, Byron Choi

  7. Property Graph Stream Processing In Action with Seraph.

    Riccardo Tommasini, Christopher Rost, Angela Bonifati, Emanuele Della Valle, Erhard Rahm, Keith W. Hare, Stefan Plantikow, Petra Selmer, Hannes Voigt

  8. MillenniumDB: A Multi-modal, Multi-model Graph Database.

    Domagoj Vrgoc, Carlos Rojas, Renzo Angles, Marcelo Arenas, Vicente Calisto, Benjamín Farias, Sebastián Ferrada, Tristan Heuer, Aidan Hogan, Gonzalo Navarro, Alexander Pinto, Juan L. Reutter, Henry Rosales-Méndez, Etienne Toussaint

  9. User-friendly, Interactive, and Configurable Explanations for Graph Neural Networks with Graph Views.

    Tingyang Chen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu Ke, Yunjun Gao

  10. The Future of Graph Analytics.

    Angela Bonifati, M. Tamer Özsu, Yuanyuan Tian, Hannes Voigt, Wenyuan Yu, Wenjie Zhang

  11. Querying Graph Databases at Scale.

    Aidan Hogan, Domagoj Vrgoc

  12. GRADES-NDA'24: 7th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA).

    Olaf Hartig, Zoi Kaoudi

IJCAI-2023

  1. Self-supervised Graph Disentangled Networks for Review-based Recommendation

    Yuyang Ren, Haonan Zhang, Qi Li, Luoyi Fu, Xinbing Wang, Chenghu Zhou

  2. A Canonicalization-Enhanced Known Fact-Aware Framework For Open Knowledge Graph Link Prediction

    Yilin Wang, Minghao Hu, Zhen Huang, Dongsheng Li, Wei Luo, Dong Yang, Xicheng Lu

  3. KDLGT: A Linear Graph Transformer Framework via Kernel Decomposition Approach

    Yi Wu, Yanyang Xu, Wenhao Zhu, Guojie Song, Zhouchen Lin, Liang Wang, Shaoguo Liu

  4. Multi-level Graph Contrastive Prototypical Clustering

    Yuchao Zhang, Yuan Yuan, Qi Wang

  5. Graph Propagation Transformer for Graph Representation Learning

    Zhe Chen, Hao Tan, Tao Wang, Tianrun Shen, Tong Lu, Qiuying Peng, Cheng Cheng, Yue Qi

  6. Graph Sampling-based Meta-Learning for Molecular Property Prediction

    Xiang Zhuang, Qiang Zhang, Bin Wu, Keyan Ding, Yin Fang, Huajun Chen

  7. A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks

    Mehrdad khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K Reddy

  8. PPAT: Progressive Graph Pairwise Attention Network for Event Causality Identification

    Zhenyu Liu, Baotian Hu, Zhenran Xu, Min Zhang

  9. Violin: Virtual Overbridge Linking for Enhancing Semi-supervised Learning on Graphs with Limited Labels

    Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau

  10. Hierarchical Transformer for Scalable Graph Learning

    Wenhao Zhu, Tianyu Wen, Guojie Song, Xiaojun Ma, Liang Wang

  11. Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation

    Yalin Yu, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang

  12. Totally Dynamic Hypergraph Neural Networks

    Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu

  13. Gapformer: Graph Transformer with Graph Pooling for Node Classification

    Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu

  14. One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction

    Jan Tönshoff, Berke Kisin, Jakob Lindner, Martin Grohe

  15. Continuous-Time Graph Learning for Cascade Popularity Prediction

    Xiaodong Lu, Shuo Ji, Le Yu, Leilei Sun, Bowen Du, Tongyu Zhu

  16. CSGCL: Community-Strength-Enhanced Graph Contrastive Learning

    Han Chen, Ziwen Zhao, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang

  17. Enabling Abductive Learning to Exploit Knowledge Graph

    Yu-Xuan Huang, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang, Zhi-Hua Zhou

  18. CONGREGATE: Contrastive Graph Clustering in Curvature Spaces

    Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu

  19. LGI-GT: Graph Transformers with Local and Global Operators Interleaving

    Shuo Yin, Guoqiang Zhong

  20. An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations

    Achille Fokoue, Ibrahim Abdelaziz, Maxwell Crouse, Shajith Ikbal, Akihiro Kishimoto, Guilherme Lima, Ndivhuwo Makondo, Radu Marinescu

  21. MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation

    Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu

  22. LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity

    Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao

  23. Globally Consistent Federated Graph Autoencoder for Non-IID Graphs

    Kun Guo, Yutong Fang, Qingqing Huang, Yuting Liang, Ziyao Zhang, Wenyu He, Liu Yang, Kai Chen, Ximeng Liu, Wenzhong Guo

  24. SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein–Protein Interaction Prediction

    Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng, Cuntai Guan, Wai Leong Tam, Xiaoli Li

  25. Minimizing Reachability Times on Temporal Graphs via Shifting Labels

    Argyrios Deligkas, Eduard Eiben, George Skretas

  26. Beyond Homophily: Robust Graph Anomaly Detection via Neural Sparsification

    Zheng Gong, Guifeng Wang, Ying Sun, Qi Liu, Yuting Ning, Hui Xiong, Jingyu Peng

  27. SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs

    Sheng Tian, Jihai Dong, Jintang Li, WENLONG ZHAO, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen

  28. Graph Neural Convection-Diffusion with Heterophily

    KAI ZHAO, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay

  29. Semi-supervised Domain Adaptation in Graph Transfer Learning

    Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong

  30. Multi-Scale Subgraph Contrastive Learning

    Yanbei Liu, Yu Zhao, Xiao Wang, Lei Geng, Zhitao Xiao

  31. Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction

    Luotao Liu, Feng Huang, Xuan Liu, Zhankun Xiong, Menglu Li, Congzhi Song, Wen Zhang

  32. Multi-View Robust Graph Representation Learning for Graph Classification

    Guanghui Ma, Chunming Hu, Ling Ge, Hong Zhang

  33. Graph-based Semi-supervised Local Clustering with Few Labeled Nodes

    Zhaiming Shen, Ming-Jun Lai, Sheng Li

  34. Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning

    Hao Dong, Zhiyuan Ning, Pengyang Wang, Ziyue Qiao, Pengfei Wang, Yuanchun Zhou, Yanjie Fu

  35. FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks

    Xinyu Fu, Irwin King

  36. Intent-aware Recommendation via Disentangled Graph Contrastive Learning

    Yuling Wang, Xiao Wang, Xiangzhou Huang, Yanhua Yu, Haoyang Li, Mengdi Zhang, Zirui Guo, Wei Wu

  37. Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction

    Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King

  38. Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention

    Hongjun Wang, Jiyuan Chen, Lun Du, Qiang Fu, Shi Han, Xuan Song

ICML-2023

  1. A Generalization of ViT/MLP-Mixer to Graphs

    Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson

  2. A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening

    Yifan Chen, Rentian Yao, Yun Yang, Jie Chen

  3. Additive Causal Bandits with Unknown Graph

    Alan Malek, Virginia Aglietti, Silvia Chiappa

  4. Alternately Optimized Graph Neural Networks

    Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang

  5. Boosting Graph Contrastive Learning via Graph Contrastive Saliency

    Chunyu Wei, Yu Wang, Bing Bai, Kai Ni, David J. Brady, LU FANG

  6. ClusterFuG: Clustering Fully connected Graphs by Multicut

    Ahmed Abbas, Paul Swoboda

  7. CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification

    Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo

  8. Conditional Graph Information Bottleneck for Molecular Relational Learning

    Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park

  9. D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching

    Xuanzhou Liu, Lin Zhang, Jiaqi Sun, Yujiu Yang, Haiqin Yang

  10. DRew: Dynamically Rewired Message Passing with Delay

    Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni

  11. Dink-Net: Neural Clustering on Large Graphs

    Yue Liu, KE LIANG, Jun Xia, sihang zhou, Xihong Yang, Xinwang Liu, Stan Z. Li

  12. Disentangled Multiplex Graph Representation Learning

    Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu

  13. Distribution Free Prediction Sets for Node Classification

    Jase Clarkson

  14. Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

    Peng XU, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu

  15. ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines

    Siyuan Chen, Pratik Pramod Fegade, Tianqi Chen, Phillip Gibbons, Todd Mowry

  16. Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation

    Joonhyuk Yang, Dongpil Shin, Hye Won Chung

  17. Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network

    Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang

  18. Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling

    Xiaohui Chen, Jiaxing He, Xu Han, Liping Liu

  19. Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian

    Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

  20. Ewald-based Long-Range Message Passing for Molecular Graphs

    Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann

  21. Exphormer: Sparse Transformers for Graphs

    Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam, Danica J. Sutherland, Ali Kemal Sinop

  22. Fast Online Node Labeling for Very Large Graphs

    Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh

  23. Featured Graph Coarsening with Similarity Guarantees

    Manoj Kumar, Anurag Sharma, Shashwat Saxena, Sandeep Kumar

  24. Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs

    YIZHEN ZHENG, He Zhang, Vincent Lee, Yu Zheng, Xiao Wang, Shirui Pan

  25. Fisher Information Embedding for Node and Graph Learning

    Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt

  26. From Hypergraph Energy Functions to Hypergraph Neural Networks

    Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf

  27. From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks

    Cai Zhou, Xiyuan Wang, Muhan Zhang

  28. GC-Flow: A Graph-Based Flow Network for Effective Clustering

    Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen

  29. GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming

    Huigen Ye, Hua Xu, Hongyan Wang, Chengming Wang, Yu Jiang

  30. GREAD: Graph Neural Reaction-Diffusion Networks

    Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho

  31. Generated Graph Detection

    Yihan Ma, Zhikun Zhang, Ning Yu, Xinlei He, Michael Backes, Yun Shen, Yang Zhang

  32. Graph Contrastive Backdoor Attacks

    Hangfan Zhang, Jinghui Chen, Lu Lin, Jinyuan Jia, Dinghao Wu

  33. Graph Generative Model for Benchmarking Graph Neural Networks

    Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov

  34. Graph Inductive Biases in Transformers without Message Passing

    Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim

  35. Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication

    AJAY KUMAR JAISWAL, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

  36. Graph Mixup with Soft Alignments

    Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou

  37. Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure

    Ryoma Sato

  38. Graph Neural Networks with Learnable and Optimal Polynomial Bases

    Yuhe Guo, Zhewei Wei

  39. Graph Neural Tangent Kernel: Convergence on Large Graphs

    Sanjukta Krishnagopal, Luana Ruiz

  40. Graph Positional Encoding via Random Feature Propagation

    Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

  41. GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks

    Yuwen Li, Miao Xiong, Bryan Hooi

  42. HOPE: High-order Graph ODE For Modeling Interacting Dynamics

    Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun

  43. Half-Hop: A graph upsampling approach for slowing down message passing

    Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Veličković, Eva L Dyer

  44. Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction

    Minghao Guo, Veronika Thost, Samuel W Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik

  45. Implicit Graph Neural Networks: A Monotone Operator Viewpoint

    Justin Baker, Qingsong Wang, Cory D Hauck, Bao Wang

  46. Improving Graph Generation by Restricting Graph Bandwidth

    Nathaniel Lee Diamant, Alex Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia

  47. Improving Graph Neural Networks with Learnable Propagation Operators

    Moshe Eliasof, Lars Ruthotto, Eran Treister

  48. InGram: Inductive Knowledge Graph Embedding via Relation Graphs

    Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang

  49. LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation

    Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu

  50. Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs

    Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco

  51. Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks

    Feng Ji, See Hian Lee, Hanyang Meng, Kai Zhao, Jielong Yang, Wee Peng Tay

  52. Linkless Link Prediction via Relational Distillation

    Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao

  53. Local Vertex Colouring Graph Neural Networks

    Shouheng Li, Dongwoo Kim, Qing Wang

  54. Modeling Dynamic Environments with Scene Graph Memory

    Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal, Emily Jin, Chengshu Li, Ruohan Zhang, Li Fei-Fei, Jiajun Wu, Silvio Savarese, Roberto Martín-Martín

  55. Multi-class Graph Clustering via Approximated Effective $p$-Resistance

    Shota Saito, Mark Herbster

  56. Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks

    Qiyu Kang, Kai Zhao, Yang Song, Sijie Wang, Wee Peng Tay

  57. On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs

    Richard A Watson, Hengrui Cai, Xinming An, Samuel McLean, Rui Song

  58. On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology

    Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein

  59. On the Connection Between MPNN and Graph Transformer

    Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang

  60. On the Expressive Power of Geometric Graph Neural Networks

    Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Lio

  61. One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding

    Daniel Severo, James Townsend, Ashish J Khisti, Alireza Makhzani

  62. Online Learning with Feedback Graphs: The True Shape of Regret

    Tomáš Kocák, Alexandra Carpentier

  63. PLay: Parametrically Conditioned Layout Generation using Latent Diffusion

    Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li

  64. Path Neural Networks: Expressive and Accurate Graph Neural Networks

    Gaspard Michel, Giannis Nikolentzos, Johannes F. Lutzeyer, Michalis Vazirgiannis

  65. Personalized Subgraph Federated Learning

    Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang

  66. Randomized Schur Complement Views for Graph Contrastive Learning

    Vignesh Kothapalli

  67. Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

    Saro Passaro, C. Lawrence Zitnick

  68. Relevant Walk Search for Explaining Graph Neural Networks

    Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Muller, Shinichi Nakajima

  69. Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching

    Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev, Zhangming Niu, Stan Z. Li

  70. Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature

    Khang Nguyen, Nong Minh Hieu, Vinh Duc NGUYEN, Nhat Ho, Stanley Osher, Tan Minh Nguyen

  71. Rotation and Translation Invariant Representation Learning with Implicit Neural Representations

    Sehyun Kwon, Joo Young Choi, Ernest K. Ryu

  72. SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning

    Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li, Ke Xu

  73. Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning

    Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

  74. SlotGAT: Slot-based Message Passing for Heterogeneous Graphs

    Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, Qing Li

  75. Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming

    Yufan Huang, C. Seshadhri, David F. Gleich

  76. Tight and fast generalization error bound of graph embedding in metric space

    Atsushi Suzuki, Atsushi Nitanda, Taiji Suzuki, jing wang, Feng Tian, Kenji Yamanishi

  77. Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering

    Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi

  78. Towards Deep Attention in Graph Neural Networks: Problems and Remedies

    Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin

  79. Towards Robust Graph Incremental Learning on Evolving Graphs

    Junwei Su, Difan Zou, Zijun Zhang, Chuan Wu

  80. Towards Understanding and Reducing Graph Structural Noise for GNNs

    Mingze Dong, Yuval Kluger

  81. Transformers Meet Directed Graphs

    Simon Geisler, Yujia Li, Daniel J Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru

  82. Understanding Oversquashing in GNNs through the Lens of Effective Resistance

    Mitchell Black, Zhengchao Wan, Amir Nayyeri, Yusu Wang

  83. Vertical Federated Graph Neural Network for Recommender System

    Peihua Mai, Yan Pang

  84. WL meet VC

    Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe

  85. Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks

    Xu Chu, Yujie Jin, Xin Wang, Shanghang Zhang, Yasha Wang, Wenwu Zhu, Hong Mei

  86. Which Invariance Should We Transfer? A Causal Minimax Learning Approach

    Mingzhou Liu, Xiangyu Zheng, Xinwei Sun, Fang Fang, Yizhou Wang

KDD-2023

  1. Kernel Ridge Regression-Based Graph Dataset Distillation

    Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, Hanghang Tong

  2. Reducing Exposure to Harmful Content via Graph Rewiring

    Corinna Coupette, Stefan Neumann, Aristides Gionis

  3. Community-based Dynamic Graph Learning for Popularity Prediction

    Shuo Ji, Xiaodong Lu, Mingzhe Liu, Leilei Sun, Chuanren Liu, Bowen Du, Hui Xiong

  4. GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network

    Ran Jia, Haoming Guo, Xiaoyuan Jin, Chao Yan, Lun Du, Xiaojun Ma, Tamara Stankovic, Marko Lozajic, Goran Zoranovic, Igor Ilic, Shi Han, Dongmei Zhang

  5. Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective

    Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng

  6. MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation

    Jiaxing Zhang, Dongsheng Luo, Hua Wei

  7. Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-Scale Disentangled Representations

    Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan

  8. What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

    Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang

  9. Efficient and Effective Edge-Wise Graph Representation Learning

    Hewen Wang, Renchi Yang, Keke Huang, Xiaokui Xiao

  10. Towards Graph-Level Anomaly Detection via Deep Evolutionary Mapping

    Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng

  11. VQNE: Variational Quantum Network Embedding with Application to Network Alignment

    Xinyu Ye, Ge Yan, Junchi Yan

  12. CARL-G: Clustering-Accelerated Representation Learning on Graphs

    William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis

  13. On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms

    Fanchen Bu, Kijung Shin

  14. Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity

    Atsushi Miyauchi, Tianyi Chen, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis

  15. Localised Adaptive Spatial-Temporal Graph Neural Network

    Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao

  16. PERT-GNN: Latency Prediction for Microservice-Based Cloud-Native Applications via Graph Neural Networks

    Da Sun Handason Tam, Yang Liu, Huanle Xu, Siyue Xie, Wing Cheong Lau

  17. Causal Effect Estimation on Hierarchical Spatial Graph Data

    Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi

  18. Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information

    Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang

  19. On Structural Expressive Power of Graph Transformers

    Wenhao Zhu, Tianyu Wen, Guojie Song, Liang Wang, Bo Zheng

  20. MGNN: Graph Neural Networks Inspired by Distance Geometry Problem

    Guanyu Cui, Zhewei Wei

  21. Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization

    Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song

  22. Learning Strong Graph Neural Networks with Weak Information

    Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, Shirui Pan

  23. Clenshaw Graph Neural Networks

    Yuhe Guo, Zhewei Wei

  24. All in One: Multi-Task Prompting for Graph Neural Networks

    Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan

  25. Certified Edge Unlearning for Graph Neural Networks

    Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang

  26. Augmenting Recurrent Graph Neural Networks with a Cache

    Guixiang Ma, Vy A Vo, Theodore L. Willke, Nesreen K. Ahmed

  27. Narrow the Input Mismatch in Deep Graph Neural Network Distillation

    Qiqi Zhou, Yanyan Shen, Lei Chen

  28. Sketch-Based Anomaly Detection in Streaming Graphs

    Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip Yu, Bryan Hooi

  29. Knowledge Graph Reasoning over Entities and Numerical Values

    Jiaxin Bai, Chen Luo, zheng li, Qingyu Yin, Bing Yin, Yangqiu Song

  30. Exploiting Relation-Aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning

    Gayeong Kim, Sookyung Kim, Ko Keun Kim, Suchan Park, Heesoo Jung, Hogun Park

  31. AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning

    Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han

  32. Context-Aware Event Forecasting via Graph Disentanglement

    Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-seng Chua

  33. Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers

    Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang

  34. GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

    Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan

  35. Grace: Graph Self-Distillation and Completion to Mitigate Degree-Relatednesses

    Hui Xu, Liyao Xiang, Femke Huang, Yuting Weng, Ruijie Xu, Xinbing Wang, Chenghu Zhou

  36. GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification

    Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai

  37. Classification of Edge-Dependent Labels of Nodes in Hypergraphs

    Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin

  38. Enhancing Graph Representations Learning with Decorrelated Propagation

    Hua Liu, Wei Jin, Xiaorui Liu, Hui Liu

  39. Meta Graph Learning for Long-Tail Recommendation

    Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang

  40. Graph Neural Bandits

    Yunzhe Qi, Yikun Ban, Jingrui He

  41. E-commerce Search via Content Collaborative Graph Neural Network

    Guipeng Xv, Chen Lin, Wanxian Guan, Jinping Gou, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng

  42. Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation

    Jin-Duk Park, Siqing Li, Xin Cao, Won-Yong Shin

  43. Knowledge Graph Self-Supervised Rationalization for Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang

  44. On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

    Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang

  45. Incremental Causal Graph Learning for Online Root Cause Analysis

    Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, Haifeng Chen

  46. Transferable Graph Structure Learning for Graph-Based Traffic Forecasting Across Cities

    Yilun Jin, Kai Chen, Qiang Yang

  47. FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework

    Raneen Younis, Zahra Ahmadi, Abdul Hakmeh, Marco Fisichella

  48. Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-Source Knowledge Graphs

    Zequn Sun, Jiacheng Huang, Jinghao Lin, Xiaozhou Xu, Qijin Chen, Wei Hu

  49. Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation

    Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen

  50. Few-Shot Low-Resource Knowledge Graph Completion with Multi-view Task Representation Generation

    Shichao Pei, Ziyi Kou, Qiannan Zhang, Xiangliang Zhang

  51. Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree

    Delvin Ce Zhang, Rex Ying, Hady W. Lauw

  52. PROSE: Graph Structure Learning via Progressive Strategy

    Huizhao Wang, Yao Fu, Tao Yu, Linghui Hu, Weihao Jiang, Shiliang Pu

  53. Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining

    Jaemin Yoo, Meng-Chieh Lee, Shubhranshu Shekhar, Christos Faloutsos

  54. Task-Equivariant Graph Few-Shot Learning

    Sungwon Kim, Junseok Lee, Namkyeong Lee, Wonjoong Kim, Seungyoon Choi, Chanyoung Park

  55. GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning

    Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li

  56. Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders

    Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong

  57. DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection

    Jiaying Wu, Bryan Hooi

  58. FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs

    Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-seng Chua, Qing He

  59. A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability

    Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du

  60. Financial Default Prediction via Motif-Preserving Graph Neural Network with Curriculum Learning

    Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou

  61. Towards Reliable Rare Category Analysis on Graphs via Individual Calibration

    Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou

  62. QTIAH-GNN: Quantity and Topology Imbalance-Aware Heterogeneous Graph Neural Network for Bankruptcy Prediction

    Yucheng Liu, Zipeng Gao, Xiangyang Liu, Pengfei Luo, Yang Yang, Hui Xiong; The Hong Kong University of Science and Technology

  63. Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling

    Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong

  64. Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems

    Peng Peng, Shengyi Ji, Zhen Tian, Hongbo Jiang, Weiguo Zheng, Xuecang Zhang

  65. Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest

    Sang-Hong Kim, Ha-Myung Park

  66. Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds

    Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, Shiliang Pu, Weihao Jiang

  67. DyTed: Disentangled Representation Learning for Discrete-Time Dynamic Graph

    Kaike Zhang, Qi Cao, Gaolin Fang, Xu Bingbing, Hongjian Zou, Huawei Shen, Xueqi Cheng

  68. Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation

    Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

  69. WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window

    Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, Jie Tang

  70. EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation

    Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang

  71. Using Motif Transitions for Temporal Graph Generation

    Penghang Liu, Ahmet Erdem Sariyuce

  72. Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks

    Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan

  73. Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks

    Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin

  74. Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models

    Kartik Sharma, Rakshit Trivedi, Rohit Sridhar, Srijan Kumar

  75. A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy

    Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang

  76. Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction

    Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, LEI BAI, Yang Wang

  77. Spatial Heterophily Aware Graph Neural Networks

    Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong; The Hong Kong University of Science and Technology

  78. Leveraging Relational Graph Neural Network for Transductive Model Ensemble

    Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, Shangsong Liang

  79. When to Pre-Train Graph Neural Networks? From Data Generation Perspective!

    Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei CHEN, Yang Yang

  80. Boosting Multitask Learning on Graphs through Higher-Order Task Affinities

    Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang

  81. Graph Neural Processes for Spatio-Temporal Extrapolation

    Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann

  82. Reconstructing Graph Diffusion History from a Single Snapshot

    Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong

  83. Generalizing Graph ODE for Learning Complex System Dynamics across Environments

    Zijie Huang, Yizhou Sun, Wei Wang

  84. B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning

    Mengyue Liu, Yun Lin, Jun Liu, Bohao Liu, Qinghua Zheng, Jin Song Dong

  85. Similarity Preserving Adversarial Graph Contrastive Learning

    Yeonjun In, Kanghoon Yoon, Chanyoung Park

  86. HomoGCL: Rethinking Homophily in Graph Contrastive Learning

    Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai

  87. Contrastive Cross-scale Graph Knowledge Synergy

    Yifei Zhang, Yankai Chen, Zixing Song, Irwin King

  88. Graph Contrastive Learning with Generative Adversarial Network

    Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai

  89. BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs

    Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang

  90. GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing

    Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu

  91. Semi-Supervised Graph Imbalanced Regression

    Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang

  92. Learning Joint Relational Co-Evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction

    Youru Li, Zhenfeng Zhu, Xiaobo Guo, Linxun Chen, Zhouyin Wang, Yinmeng Wang, Bing Han, Yao Zhao

  93. A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection

    Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li

  94. Commonsense Knowledge Graph towards Supper APP and Its Applications in Alipay

    Xiaoling Zang, Binbin Hu, Chu Jun, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong

  95. Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering

    Xujia Li, Yuan Li, Xueying Mo, Hebing Xiao, Yanyan Shen, Lei Chen; Hong Kong University of Science and Technology

  96. DGI: An Easy and Efficient Framework for GNN Model Evaluation

    Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang

  97. Learning Multivariate Hawkes Process via Graph Recurrent Neural Network

    Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park

  98. HUGE: Huge Unsupervised Graph Embeddings with TPUs

    Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi

  99. Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs

    Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji, Fengli Xiao, Chunming Hu, Zhiguang Shan

  100. IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

    Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu

  101. MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification

    Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen

  102. Graph Learning in Physical-Informed Mesh-Reduced Space for Real-World Dynamic Systems

    Yeping Hu, Bo Lei, Victor M. Castillo

  103. Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs

    Tingyan Xiang, Ao Li, Yugang Ji, Dong Li

  104. TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation

    Wenxin Tai, Bin Chen, Fan Zhou, Ting Zhong, Goce Trajcevski, Yong Wang, Kai Chen

  105. Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering

    Xinyue Hu, Lin Gu, Qiyuan An, Zhang Mengliang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu

  106. Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems

    Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang

  107. Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications

    Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi

  108. PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation

    Xuewu Jiao, Weibin Li, Xinxuan Wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu

  109. Adaptive Graph Contrastive Learning for Recommendation

    Yangqin Jiang, Chao Huang, Lianghao Xia

  110. Real Time Index and Search Across Large Quantities of GNN Experts For Low Latency Online Learning

    Johan Zhi Kang Kok, Sien Yi Tan, Bingsheng He, Zhen Zhang

  111. ILRoute: A Graph-based Imitation Learning Method to Unveil Riders’ Routing Strategies in Food Delivery Service

    Tao Feng, Huan Yan, Huandong Wang, Wenzhen Huang, Yuyang Han, Hongsen Liao, Jinghua Hao, Yong Li

  112. Deep Transfer Learning for City-Scale Cellular Traffic Generation through Urban Knowledge Graph

    Zhang Shiyuan, Tong Li, Shuodi Hui, Guangyu Li, Yanping Liang, Li Yu, Depeng Jin, Yong Li

SIGIR-2023

  1. Adaptive Graph Representation Learning for Next POI Recommendation

    Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li, Jiadi Yu

  2. Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering

    Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang

  3. Candidate–aware Graph Contrastive Learning for Recommendation

    Wei He, Guohao Sun, Jinhu Lu, Xiu Susie Fang

  4. Continual Learning on Dynamic Graphs via Parameter Isolation

    Peiyan Zhang, Yuchen Yan, Chaozhuo Li, Senzhang Wang, Xing Xie, Guojie Song, Sunghun Kim

  5. Contrastive Learning for Signed Bipartite Graphs

    Zeyu Zhang, Jiamou Liu, Kaiqi Zhao, Song Yang, Xianda Zheng, Yifei Wang

  6. Decoupled Hyperbolic Graph Attention Network for Cross-domain Named Entity Recognition

    Jingyun Xu, Yi Cai

  7. Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation

    Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang, Chenghu Zhou

  8. DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning

    Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao

  9. Dynamic Graph Evolution Learning for Recommendation

    Haoran Tang, Shiqing Wu, Guandong Xu, Qing Li

  10. Generative-Contrastive Graph Learning for Recommendation

    Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang

  11. Graph Masked Autoencoder for Sequential Recommendation

    Yaowen Ye, Lianghao Xia, Chao Huang

  12. Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation

    Qian Chen, Zhiqiang Guo, Jianjun Li, Guohui Li

  13. Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning

    Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu

  14. LightGT: A Light Graph Transformer for Multimedia Recommendation

    Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie, Tat-Seng Chua

  15. M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation

    Zepeng Huai, Yuji Yang, Mengdi Zhang, Zhongyi Zhang, Yichun Li, Wei Wu

  16. Graph Transformer for Recommendation

    Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang

  17. Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation

    Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan, Fanyu Kong

  18. Multi-order Matched Neighborhood Consistent Graph Alignment in a Union Vector Space

    Wei Tang, Haifeng Sun, Jingyu Wang, Qi Qi, Jing Wang, Hao Yang, Shimin Tao

  19. Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation

    Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen, Feida Zhu

  20. Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network

    Ran Li, Liang Zhang, Guannan Liu, Junjie Wu

  21. Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion

    Linhao Luo, Reza Haffari, Yuan Fang Li, Shirui Pan

  22. Relation-Aware Multi-Positive Contrastive Knowledge Graph Completion with Embedding Dimension Scaling

    Bin Shang, Yinliang Zhao, Di Wang, Jun Liu

  23. Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction

    Yunzhi Yao, Shengyu Mao, Ningyu Zhang, Xiang Chen, Shumin Deng, Xi Chen, Huajun Chen

  24. Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph

    Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong

  25. Session Search with Pre-trained Graph Classification Model

    Shengjie Ma, Chong Chen, Jiaxin Mao, Qi Tian, Xuhui Jiang

  26. Spatio-Temporal Hypergraph Learning for Next POI Recommendation

    Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li, Wei Chu

  27. StreamE: Learning to Update Representations for Temporal Knowledge Graphs in Streaming Scenarios

    Jiasheng Zhang, Jie Shao, Bin Cui

  28. Subgraph Search over Neural-Symbolic Graphs

    Ye Yuan, Delong Ma, Anbiao Wu, Jianbin Qin

  29. Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis

    Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang

  30. Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs

    Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin, Enhong Chen

  31. Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation

    Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang

  32. Weighted Knowledge Graph Embedding

    Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang, Zhulin An, Fei Wang, Yongjun Xu

  33. DeviceGPT: A Generative Pre-Training Transformer on the Heterogenous Graph for Internet of Things

    Yimo Ren, Jinfa Wang, Hong Li, Hongsong Zhu, Limin Sun

  34. DocGraphLM: Documental graph language model for information extraction

    Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh, Kang Gu, Sameena Shah

  35. Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning

    Hongxiang Lin, Ruiqi Jia, Xiaoqing Lyu

  36. Graph Collaborative Signals Denoising and Augmentation for Recommendation

    Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu

  37. Hierarchical Type Enhanced Negative Sampling for Knowledge Graph Embedding

    Zhenzhou Lin, Zishuo Zhao, Jingyou Xie, Ying Shen

  38. HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraphs

    Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng

  39. MDKG: Graph-Based Medical Knowledge-Guided Dialogue Generation

    Usman Naseem, Surendrabikram Thapa, Qi Zhang, Liang Hu, Mehwish Nasim

  40. Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion

    Donghan Yu, Yiming Yang

  41. Sharpness-Aware Graph Collaborative Filtering

    Huiyuan Chen, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Junpeng Wang, Vivian Lai, Mahashweta Das, Hao Yang

  42. TrustSGCN: Learning Trustworthiness on Edge Signs for Effective Signed Graph Convolutional Networks

    Min-Jeong Kim, Yeon-Chang Lee, Sang-Wook Kim

  43. Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework

    Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi

  44. WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering

    Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King

NeurIPS-2023

  1. (Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More

    Jan Schuchardt, Yan Scholten, Stephan Günnemann

  2. 4D Panoptic Scene Graph Generation

    Jingkang Yang, Jun CEN, WENXUAN PENG, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu

  3. A Comparative Study of Graph Structure Learning: Benchmark and Analysis

    Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Yu

  4. A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking

    Hao Yan, Chaozhuo Li, Ruosong Long, Chao Yan, Jianan Zhao, Wenwen Zhuang, Jun Yin, Peiyan Zhang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Lichao Sun, Xing Xie, Senzhang Wang

  5. A Fractional Graph Laplacian Approach to Oversmoothing

    Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok

  6. A Meta Learning Model for Scalable Hyperbolic Graph Neural Networks

    Nurendra Choudhary, Nikhil Rao, Chandan Reddy

  7. A Metadata-Driven Approach to Understand Graph Neural Networks

    Ting Wei Li, Qiaozhu Mei, Jiaqi Ma

  8. A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

    Vignesh Kothapalli, Tom Tirer, Joan Bruna

  9. A graphon-signal analysis of graph neural networks

    Ron Levie

  10. A new perspective on building efficient and expressive 3D equivariant graph neural networks

    weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma

  11. A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

    Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

  12. AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity

    Jingyuan Li, Leo Scholl, Trung Le, Amy Orsborn, Eli Shlizerman

  13. Accelerating Molecular Graph Neural Networks via Knowledge Distillation

    Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger

  14. Act As You Wish: Fine-grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs

    Peng Jin, Yang Wu, Yanbo Fan, Zhongqian Sun, Wei Yang, Li Yuan

  15. Adversarial Robustness in Graph Neural Networks: A Hamiltonian Energy Conservation Approach

    Kai Zhao, Yang Song, Qiyu Kang, Rui She, Sijie Wang, Wee Peng Tay

  16. Adversarial Training for Graph Neural Networks

    Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

  17. Affinity-Aware Graph Networks

    Ameya Velingker, Ali Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi

  18. An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations

    Haoran Yang, Xiangyu Zhao, Yicong Li, Hongxu Chen, Guandong Xu

  19. Approximately Equivariant Graph Networks

    Ningyuan Huang, Ron Levie, Soledad Villar

  20. Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning

    Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang

  21. AutoGO: Automated Computation Graph Optimization for Neural Network Evolution

    Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang, Wei Lu, Shangling Jui, CHUNHUA ZHOU, Fengyu Sun, Di Niu

  22. Bayesian Optimisation of Functions on Graphs

    Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong

  23. Better with Less: A Data-Centric Prespective on Pre-Training Graph Neural Networks

    *Jiarong Xu, Renhong Huang, XIN JIANG, Yuxuan Cao, Carl Yang, Chunping Wang, YANG YANG*

  24. Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence

    Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

  25. CAT-Walk: Inductive Hypergraph Learning via Set Walks

    Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer

  26. Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs

    Yeyuan Chen, Dingmin Wang

  27. Can Language Models Solve Graph Problems in Natural Language?

    Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov

  28. Certifiably Robust Graph Contrastive Learning

    Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang

  29. Characterization and Learning of Causal Graphs with Small Conditioning Sets

    Murat Kocaoglu

  30. Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond

    Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova

  31. CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs

    Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam

  32. Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions

    Duligur Ibeling, Thomas Icard

  33. Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints

    Jiaxin Bai, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song

  34. Curvature Filtrations for Graph Generative Model Evaluation

    Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck

  35. D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion

    Jialin Chen, Shirley Wu, Abhijit Gupta, Rex Ying

  36. DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization

    Zhiqing Sun, Yiming Yang

  37. Data-Centric Learning from Unlabeled Graphs with Diffusion Model

    Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang

  38. Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment

    Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann

  39. Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems

    Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré

  40. Deep Insights into Noisy Pseudo Labeling on Graph Data

    Botao WANG, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung

  41. Demystifying Oversmoothing in Attention-Based Graph Neural Networks

    Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie

  42. Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

    Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

  43. Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs

    CHEN SHENGYUAN, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun

  44. Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection

    Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Ozgur, Olgica Milenkovic

  45. Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks

    Xin Yan, Qiang He, Hui Fang

  46. Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data

    Saptarshi Roy, Raymond K. W. Wong, Yang Ni

  47. Directional Diffusion Model for Graph Representation Learning

    Run Yang, Yuling Yang, Fan Zhou, Qiang Sun

  48. Does Graph Distillation See Like Vision Dataset Counterpart?

    Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, Jianxin Li

  49. Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

    Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng

  50. Efficient Learning of Linear Graph Neural Networks via Node Subsampling

    Seiyun Shin, Ilan Shomorony, Han Zhao

  51. Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph

    Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec

  52. Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization

    Haonan Yuan, Qingyun Sun, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li

  53. Equivariant Neural Operator Learning with Graphon Convolution

    Chaoran Cheng, Jian Peng

  54. Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

    Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang

  55. Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking

    Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin

  56. Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

    Junfeng Fang, Wei Liu, Xiang Wang, Zemin Liu, An Zhang, Yuan Gao, Xiangnan He

  57. Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts

    Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova

  58. Evaluating Self-Supervised Learning for Molecular Graph Embeddings

    Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

  59. Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes

    Cai Zhou, Xiyuan Wang, Muhan Zhang

  60. Fair Graph Distillation

    Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu

  61. Fast Approximation of Similarity Graphs with Kernel Density Estimation

    Peter Macgregor, He Sun

  62. FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks

    Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong

  63. Fine-grained Expressivity of Graph Neural Networks

    Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris

  64. FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective

    Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu

  65. Fragment-based Pretraining and Finetuning on Molecular Graphs

    Kha-Dinh Luong, Ambuj K Singh

  66. From Trainable Negative Depth to Edge Heterophily in Graphs

    Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong

  67. Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge

    Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

  68. Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications

    Xinyu Ma, Xu Chu, Yasha Wang, Yang Lin, Junfeng Zhao, Liantao Ma, Wenwu Zhu

  69. GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection

    Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li

  70. GALOPA: Graph Transport Learning with Optimal Plan Alignment

    Yejiang Wang, Yuhai Zhao, Daniel Zhengkui Wang, Ling Li

  71. GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning

    Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu

  72. GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection

    Namyong Park, Ryan Rossi, Xing Wang, Antoine Simoulin, Nesreen K. Ahmed, Christos Faloutsos

  73. GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels

    Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan

  74. Generalised f-Mean Aggregation for Graph Neural Networks

    Ryan Kortvelesy, Steven D Morad, Amanda Prorok

  75. Generative Pre-Training of Spatio-Temporal Graph Neural Networks

    Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang

  76. Geometric Analysis of Matrix Sensing over Graphs

    Haixiang Zhang, Ying Chen, Javad Lavaei

  77. Graph Clustering with Graph Neural Networks

    Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller

  78. Graph Convolutional Kernel Machine versus Graph Convolutional Networks

    Zhihao Wu, Zhao Zhang, Jicong Fan

  79. Graph Denoising Diffusion for Inverse Protein Folding

    Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang

  80. Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

    Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang "Atlas" Wang

  81. Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis

    Abhinav Nippani, Dongyue Li, Haotian Ju, Haris Koutsopoulos, Hongyang Zhang

  82. Graph of Circuits with GNN for Exploring the Optimal Design Space

    Aditya Shahane, Saripilli Swapna Manjiri, Sandeep Kumar, Ankesh Jain

  83. Graph-Structured Gaussian Processes for Transferable Graph Learning

    Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He

  84. GraphACL: Simple Asymmetric Contrastive Learning of Graphs

    Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang

  85. GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

    Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang

  86. GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search

    Xiao Zang, Miao Yin, Jinqi Xiao, Saman Zonouz, Bo Yuan

  87. GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Node Patching

    Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye

  88. Graphs Contrastive Learning with Stable and Scalable Spectral Encoding

    Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi

  89. How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits

    Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari

  90. HyTrel: Hypergraph-enhanced Tabular Data Representation Learning

    Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis

  91. Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion

    Shengqiong Wu, Hao Fei, Hanwang Zhang, Tat-Seng Chua

  92. Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network

    Yixiao Zhou, Ruiqi Jia, Xiaoqing Lyu, Yumeng Zhao, Hefeng Quan, Hongxiang Lin

  93. Interpretable Graph Networks Formulate Universal Algebra Conjectures

    Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero

  94. Interpretable Prototype-based Graph Information Bottleneck

    Sangwoo Seo, Sungwon Kim, Chanyoung Park

  95. Intervention Generalization: A View from Factor Graph Models

    Gecia Bravo-Hermsdorff, David Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva

  96. Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy

    Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li

  97. Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

    Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji

  98. LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embedding

    Ningyi Liao, Siqiang Luo, Xiang Li, Jieming Shi

  99. Language Semantic Graph Guided Data-Efficient Learning

    Wenxuan Ma, Shuang Li, lincan Cai, Jingxuan Kang

  100. Large sample spectral analysis of graph-based multi-manifold clustering

    Nicolas Garcia Trillos, Pengfei He, Chenghui Li

  101. Latent Graph Inference with Limited Supervision

    Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu

  102. Learning Efficient Surrogate Dynamic Models with Graph Spline Networks

    Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park

  103. Learning Invariant Representations of Graph Neural Networks via Cluster Generalization

    Xiao Wang, Donglin Xia, Nian Liu, Chuan Shi

  104. Learning Large Graph Property Prediction via Graph Segment Training

    Kaidi Cao, Phitchaya Phothilimtha, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi

  105. Learning Latent Causal Graphs with Unknown Interventions

    Yibo Jiang, Bryon Aragam

  106. Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction

    Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen

  107. Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion

    Kunxun Qi, Jianfeng Du, Hai Wan

  108. Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets

    Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron Courville, Yoshua Bengio, Ling Pan

  109. Limits, approximation and size transferability for GNNs on sparse graphs via graphops

    Thien Le, Stefanie Jegelka

  110. LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference

    Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding

  111. Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT

    Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He

  112. LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees

    Shangyuan LIU, Linglingzhi Zhu, Anthony Man-Cho So

  113. Lovász Principle for Unsupervised Graph Representation Learning

    Ziheng Sun, Chris Ding, Jicong Fan

  114. MAG-GNN: Reinforcement Learning Boosted Graph Neural Network

    Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang

  115. MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy

    Honghua Dong, Jiawei Xu, Yu Yang, Rui Zhao, Shiwen Wu, Chun Yuan, Xiu Li, Chris Maddison, Lei Han

  116. Mitigating the Popularity Bias in Graph-based Collaborative Filtering

    Yifei Zhang, Hao Zhu, yankai Chen, Zixing Song, Piotr Koniusz, Irwin King

  117. MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data

    Tianyu Liu, Yuge Wang, Rex Ying, Hongyu Zhao

  118. Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion

    Hyuna Cho, Minjae Jeong, Sooyeon Jeon, Sungsoo Ahn, Won Hwa Kim

  119. Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum

    Yijian Qin, Xin Wang, Ziwei Zhang, Hong Chen, Wenwu Zhu

  120. Network Regression with Graph Laplacians

    Yidong Zhou, Hans-Georg Müller

  121. Neural Graph Generation from Graph Statistics

    Kiarash Zahirnia, Oliver Schulte, Mark Coates, Yaochen Hu

  122. Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem

    Tal Amir, Steven Gortler, Ilai Avni, Ravina Ravina, Nadav Dym

  123. Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data

    Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song

  124. NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics

    Anwar Said, Roza Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer, Catie Chang, Xenofon Koutsoukos

  125. Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems

    Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen

  126. No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning

    Zixing Song, Yifei Zhang, Irwin King

  127. On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data

    Federico Errica

  128. On Learning Necessary and Sufficient Causal Graphs

    Hengrui Cai, Yixin Wang, Michael Jordan, Rui Song

  129. On the Ability of Graph Neural Networks to Model Interactions Between Vertices

    Noam Razin, Tom Verbin, Nadav Cohen

  130. On the Minimax Regret for Online Learning with Feedback Graphs

    Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi

  131. OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

    Zhou Zhiyao, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Can Wang, Yan Feng, Chun Chen

  132. Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning

    Zixing Song, Yifei Zhang, Irwin King

  133. Optimality of Message-Passing Architectures for Sparse Graphs

    Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

  134. Outlier-Robust Gromov Wasserstein for Graph Data

    Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So

  135. PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis

    Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen, Nesreen K. Ahmed, Ali Jannesari

  136. PRODIGY: Enabling In-context Learning Over Graphs

    Qian Huang, Hongyu Ren, Peng Chen, Gregor Kržmanc, Daniel Zeng, Percy Liang, Jure Leskovec

  137. Partial Multi-Label Learning with Probabilistic Graphical Disambiguation

    Jun-Yi Hang, Min-Ling Zhang

  138. Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference

    Ran Ran, Nuo Xu, Tao Liu, Wei Wang, Gang Quan, Wujie Wen

  139. PlanE: Representation Learning over Planar Graphs

    Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, Ismail Ceylan

  140. Practical Contextual Bandits with Feedback Graphs

    Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro

  141. Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily

    Langzhang Liang, Xiangjing Hu, Zenglin Xu, Zixing Song, Irwin King

  142. Private subgraph counting using alternatives to global sensitivity

    Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti

  143. Provable Training for Graph Contrastive Learning

    Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi

  144. Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals

    Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Kovalsky, Minjeong Kim, Won Hwa Kim, Guorong Wu

  145. Recurrent Temporal Revision Graph Networks

    Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou

  146. Relational Curriculum Learning for Graph Neural Network

    Zheng Zhang, Junxiang Wang, Liang Zhao

  147. Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules

    ZHIYUAN LIU, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua

  148. SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

    Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao

  149. Self-supervised Graph Neural Networks via Low-Rank Decomposition

    Liang Yang, Runjie Shi, Qiuliang Zhang, bingxin niu, Zhen Wang, Chuan Wang, Xiaochun Cao

  150. Sheaf Hypergraph Networks

    Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió

  151. Simplifying and Empowering Transformers for Large-Graph Representations

    Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan

  152. Sparse Graph Learning from Spatiotemporal Time Series

    Andrea Cini, Daniele Zambon, Cesare Alippi

  153. Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue', Haoyang Li, Wenwu Zhu

  154. Structure preserving reversible and irreversible bracket dynamics for deep graph neural networks

    Anthony Gruber, Kookjin Lee, Nathaniel Trask

  155. Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data

    Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan

  156. SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network

    Yuting Hu, Jiajie Li, Florian Klemme, Gi-Joon Nam, Tengfei Ma, Hussam Amrouch, Jinjun Xiong

  157. TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph

    Xueyuan Lin, Chengjin Xu, Haihong E, Fenglong Su, Gengxian Zhou, Tianyi Hu, Ningyuan Li, Mingzhi Sun, Haoran Luo

  158. Tailoring Self-Attention for Graph via Rooted Subtrees

    Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin

  159. Taming Local Effects in Graph-based Spatiotemporal Forecasting

    Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi

  160. TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery

    Jialin Chen, Rex Ying

  161. Temporal Graph Benchmark for Machine Learning on Temporal Graphs

    Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael Bronstein, Guillaume Rabusseau, Reihaneh Rabbany

  162. The Graphical Matrix Pencil Method: Exchangeable Distributions with Prescribed Subgraph Densities

    Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz

  163. The expressive power of pooling in Graph Neural Networks

    Filippo Maria Bianchi, Veronica Lachi

  164. Towards Better Dynamic Graph Learning: New Architecture and Unified Library

    Le Yu, Leilei Sun, Bowen Du, Weifeng Lv

  165. Towards Label Position Bias in Graph Neural Networks

    Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu Aggarwal, Jiliang Tang

  166. Towards Self-Interpretable Graph-Level Anomaly Detection

    Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan

  167. TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs

    Phitchaya Phothilimtha, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Charith Mendis, Bryan Perozzi

  168. Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks

    Jun Yin, Senzhang Wang, Hao Yan, Chaozhuo Li, Jianxun Lian

  169. Transformers over Directed Acyclic Graphs

    Yuankai Luo, Veronika Thost, Lei Shi

  170. Truncated Affinity Maximization for Graph Anomaly Detection

    Hezhe Qiao, Guansong Pang

  171. UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction

    Yansong Ning, Hao Liu, Hao Wang, Zhenyu Zeng, Hui Xiong

  172. Uncertainty Quantification over Graph with Conformalized Graph Neural Networks

    Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec

  173. Universal Prompt Tuning for Graph Neural Networks

    Taoran Fang, Yunchao Zhang, YANG YANG, Chunping Wang, Lei Chen

  174. Unleashing the Power of Graph Data Augmentation on Covariate Shift

    Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He

  175. Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen, Wenwu Zhu

  176. V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs

    Jun Yin, Senzhang Wang, Chaozhuo Li, Xing Xie, Jianxin Wang

  177. Variational Annealing on Graphs for Combinatorial Optimization

    Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner

  178. Video-Mined Task Graphs for Keystep Recognition in Instructional Videos

    Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman

  179. WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding

    Yanchao Tan, Zihao Zhou, Hang Lv, Weiming Liu, Carl Yang

  180. What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding

    Nicolas Keriven, Samuel Vaiter

  181. When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability

    Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup

  182. Zero-One Laws of Graph Neural Networks

    Sam Adam-Day, Iliant, Ismail Ceylan

  183. [Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification

    Ermin Omeragic, Vuk Đuranović

  184. [Re] On Explainability of Graph Neural Networks via Subgraph Explorations

    Yannik Mahlau, Lukas Berg, Leonie Kayser

CIKM-2023

  1. Knowledge Graphs for Knowing More and Knowing for Sure

    Steffen Staab

  2. Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs

    Medina Andresel, Trung-Kien Tran, Csaba Domokos, Pasquale Minervini, Daria Stepanova

  3. GraphERT-- Transformers-based Temporal Dynamic Graph Embedding

    Moran Beladev, Gilad Katz, Lior Rokach, Uriel Singer, Kira Radinsky

  4. Faster Approximation Algorithms for Parameterized Graph Clustering and Edge Labeling

    Vedangi Bengali, Nate Veldt

  5. Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer

    Wendong Bi, Xueqi Cheng, Bingbing Xu, Xiaoqian Sun, Li Xu, Huawei Shen

  6. How Expressive are Graph Neural Networks in Recommendation?

    Xuheng Cai, Lianghao Xia, Xubin Ren, Chao Huang

  7. Learning Pair-Centric Representation for Link Sign Prediction with Subgraph

    Jushuo Chen, Feifei Dai, Xiaoyan Gu, Haihui Fan, Jiang Zhou, Bo Li, Weiping Wang

  8. Can Knowledge Graphs Simplify Text?

    Anthony Colas, Haodi Ma, Xuanli He, Yang Bai, Daisy Zhe Wang

  9. Cross-heterogeneity Graph Few-shot Learning

    Pengfei Ding, Yan Wang, Guanfeng Liu

  10. Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training

    Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, Philip S. Yu

  11. Spatial-Temporal Graph Boosting Networks: Enhancing Spatial-Temporal Graph Neural Networks via Gradient Boosting

    Yujie Fan, Chin-Chia Michael Yeh, Huiyuan Chen, Yan Zheng, Liang Wang, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Wei Zhang

  12. BOMGraph: Boosting Multi-scenario E-commerce Search with a Unified Graph Neural Network

    Shuai Fan, Jinping Gou, Yang Li, Jiaxing Bai, Chen Lin, Wanxian Guan, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng

  13. Cognitive-inspired Graph Redundancy Networks for Multi-source Information Fusion

    Yao Fu, Junhong Wan, Junlan Yu, Weihao Jiang, Shiliang Pu

  14. On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks

    Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans, Fragkiskos D. Malliaros

  15. Homophily-enhanced Structure Learning for Graph Clustering

    Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu

  16. KG4Ex: An Explainable Knowledge Graph-Based Approach for Exercise Recommendation

    Quanlong Guan, Fang Xiao, Xinghe Cheng, Liangda Fang, Ziliang Chen, Guanliang Chen, Weiqi Luo

  17. Targeted Shilling Attacks on GNN-based Recommender Systems

    Sihan Guo, Ting Bai, Weihong Deng

  18. Interpretable Fake News Detection with Graph Evidence

    Hao Guo, Weixin Zeng, Jiuyang Tang, Xiang Zhao

  19. Towards Fair Graph Neural Networks via Graph Counterfactual

    Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang

  20. Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning

    Xinrui He, Tianxin Wei, Jingrui He

  21. Celebrity-aware Graph Contrastive Learning Framework for Social Recommendation

    Zheng Hu, Satoshi Nakagawa, Liang Luo, Yu Gu, Fuji Ren

  22. HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion

    Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, Jeff Z. Pan

  23. Enhanced Template-Free Reaction Prediction with Molecular Graphs and Sequence-based Data Augmentation

    Haozhe Hu, Yongquan Jiang, Yan Yang, Jim X. Chen

  24. Independent Distribution Regularization for Private Graph Embedding

    Qi Hu, Yangqiu Song

  25. Liberate Pseudo Labels from Over-Dependence: Label Information Migration on Sparsely Labeled Graphs

    Zhihui Hu, Yao Fu, Hong Zhao, Xiaoyu Cai, Weihao Jiang, Shiliang Pu

  26. Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical Pruning

    Lucas Jarnac, Miguel Couceiro, Pierre Monnin

  27. Robust Graph Clustering via Meta Weighting for Noisy Graphs

    Hyeonsoo Jo, Fanchen Bu, Kijung Shin

  28. A Model-Agnostic Method to Interpret Link Prediction Evaluation of Knowledge Graph Embeddings

    Narayanan Asuri Krishnan, Carlos R. Rivero

  29. A Re-evaluation of Deep Learning Methods for Attributed Graph Clustering

    Xinying Lai, Dingming Wu, Christian S. Jensen, Kezhong Lu

  30. DuoGAT: Dual Time-oriented Graph Attention Networks for Accurate, Efficient and Explainable Anomaly Detection on Time-series

    Jongsoo Lee, Byeongtae Park, Dong-Kyu Chae

  31. GUARD: Graph Universal Adversarial Defense

    Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang

  32. ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks

    Yiqiao Li, Jianlong Zhou, Yifei Dong, Niusha Shafiabady, Fang Chen

  33. Heterogeneous Temporal Graph Neural Network Explainer

    Jiazheng Li, Chunhui Zhang, Chuxu Zhang

  34. Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation

    Qingyao Li, Wei Xia, Li'ang Yin, Jian Shen, Renting Rui, Weinan Zhang, Xianyu Chen, Ruiming Tang, Yong Yu

  35. Contrastive Representation Learning Based on Multiple Node-centered Subgraphs

    Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao

  36. Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs

    Junlin Li, Yueheng Sun, Minglai Shao

  37. THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks

    Yilin Li, Jiaqi Zhu, Congcong Zhang, Yi Yang, Jiawen Zhang, Ying Qiao, Hongan Wang

  38. Retrieving GNN Architecture for Collaborative Filtering

    Fengqi Liang, Huan Zhao, Zhenyi Wang, Wei Fang, Chuan Shi

  39. printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning

    Hao-Lun Lin, Jyun-Yu Jiang, Ming-Hao Juan, Pu-Jen Cheng

  40. MATA: Combining Learnable Node Matching with A Algorithm for Approximate Graph Edit Distance Computation**

    Junfeng Liu, Min Zhou, Shuai Ma, Lujia Pan

  41. ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding

    Zixuan Liu, Gaurush Hiranandani, Kun Qian, Edward W. Huang, Yi Xu, Belinda Zeng, Karthik Subbian, Sheng Wang

  42. SMEF: Social-aware Multi-dimensional Edge Features-based Graph Representation Learning for Recommendation

    Xiao Liu, Shunmei Meng, Qianmu Li, Lianyong Qi, Xiaolong Xu, Wanchun Dou, Xuyun Zhang

  43. Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph

    Yi Liu, Hongrui Xuan, Bohan Li, Meng Wang, Tong Chen, Hongzhi Yin

  44. BRep-BERT: Pre-training Boundary Representation BERT with Sub-graph Node Contrastive Learning

    Yunzhong Lou, Xueyang Li, Haotian Chen, Xiangdong Zhou

  45. Timestamps as Prompts for Geography-Aware Location Recommendation

    Yan Luo, Haoyi Duan, Ye Liu, Fu-Lai Chung

  46. Improving Long-Tail Item Recommendation with Graph Augmentation

    Sichun Luo, Chen Ma, Yuanzhang Xiao, Linqi Song

  47. Multi-scale Graph Pooling Approach with Adaptive Key Subgraph for Graph Representations

    Yiqin Lv, Zhiliang Tian, Zheng Xie, Yiping Song

  48. A Graph Neural Network Model for Concept Prerequisite Relation Extraction

    Debjani Mazumder, Jiaul H. Paik, Anupam Basu

  49. Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification

    Arpit Merchant, Carlos Castillo

  50. Rule-based Knowledge Graph Completion with Canonical Models

    Simon Ott, Patrick Betz, Daria Stepanova, Mohamed H. Gad-Elrab, Christian Meilicke, Heiner Stuckenschmidt

  51. A Retrieve-and-Read Framework for Knowledge Graph Link Prediction

    Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su

  52. Bi-channel Multiple Sparse Graph Attention Networks for Session-based Recommendation

    Shutong Qiao, Wei Zhou, Junhao Wen, Hongyu Zhang, Min Gao

  53. ELTRA: An Embedding Method based on Learning-to-Rank to Preserve Asymmetric Information in Directed Graphs

    Masoud Rehyani Hamedani, Jin-Su Ryu, Sang-Wook Kim

  54. Dual-Process Graph Neural Network for Diversified Recommendation

    Yuanyi Ren, Hang Ni, Yingxue Zhang, Xi Wang, Guojie Song, Dong Li, Jianye Hao

  55. Incremental Graph Classification by Class Prototype Construction and Augmentation

    Yixin Ren, Li Ke, Dong Li, Hui Xue, Zhao Li, Shuigeng Zhou

  56. Seq-HyGAN: Sequence Classification via Hypergraph Attention Network

    Khaled Mohammed Saifuddin, Corey May, Farhan Tanvir, Muhammad Ifte Khairul Islam, Esra Akbas

  57. Transferable Structure-based Adversarial Attack of Heterogeneous Graph Neural Network

    Yu Shang, Yudong Zhang, Jiansheng Chen, Depeng Jin, Yong Li

  58. Improving Graph Domain Adaptation with Network Hierarchy

    Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng

  59. GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction

    Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu

  60. Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning

    Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li

  61. Towards Fair Financial Services for All: A Temporal GNN Approach for Individual Fairness on Transaction Networks

    Zixing Song, Yuji Zhang, Irwin King

  62. Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data

    Xiao Tan, Yangyang Shen, Meng Wang, Beilun Wang

  63. Explainable Spatio-Temporal Graph Neural Networks

    Jiabin Tang, Lianghao Xia, Chao Huang

  64. Citation Intent Classification and Its Supporting Evidence Extraction for Citation Graph Construction

    Hong-Jin Tsai, An-Zi Yen, Hen-Hsen Huang, Hsin-Hsi Chen

  65. Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation

    Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang

  66. GraphFADE: Field-aware Decorrelation Neural Network for Graphs with Tabular Features

    Junhong Wan, Yao Fu, Junlan Yu, Weihao Jiang, Shiliang Pu, Ruiheng Yang

  67. UrbanFloodKG: An Urban Flood Knowledge Graph System for Risk Assessment

    Yu Wang, Feng Ye, Binquan Li, Gaoyang Jin, Dong Xu, Fengsheng Li

  68. Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation

    Shuang Wang, Bahaeddin Eravci, Rustam Guliyev, Hakan Ferhatosmanoglu

  69. Node-dependent Semantic Search over Heterogeneous Graph Neural Networks

    Zhenyi Wang, Huan Zhao, Fengqi Liang, Chuan Shi

  70. Dual Intents Graph Modeling for User-centric Group Discovery

    Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang

  71. SplitGNN: Spectral Graph Neural Network for Fraud Detection against Heterophily

    Bin Wu, Xinyu Yao, Boyan Zhang, Kuo-Ming Chao, Yinsheng Li

  72. DPGN: Denoising Periodic Graph Network for Life Service Recommendation

    Hao Xu, Huixuan Chi, Danyang Liu, Sheng Zhou, Mengdi Zhang

  73. A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge

    Kailai Yang, Tianlin Zhang, Shaoxiong Ji, Sophia Ananiadou

  74. Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning

    Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

  75. Causality-guided Graph Learning for Session-based Recommendation

    Dianer Yu, Qian Li, Hongzhi Yin, Guandong Xu

  76. MUSE: Multi-view Contrastive Learning for Heterophilic Graphs via Information Reconstruction

    Mengyi Yuan, Minjie Chen, Xiang Li

  77. AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange

    Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li

  78. RDGSL: Dynamic Graph Representation Learning with Structure Learning

    Siwei Zhang, Yun Xiong, Yao Zhang, Yiheng Sun, Xi Chen, Yizhu Jiao, Yangyong Zhu

  79. iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation

    Siwei Zhang, Yun Xiong, Yao Zhang, Xixi Wu, Yiheng Sun, Jiawei Zhang

  80. Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs

    Haozhen Zhang, Xueting Han, Xi Xiao, Jing Bai

  81. AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities

    Jingdan Zhang, Jiaan Wang, Xiaodan Wang, Zhixu Li, Yanghua Xiao

  82. Efficient Exact Minimum k-Core Search in Real-World Graphs

    Qifan Zhang, Shengxin Liu

  83. HST-GT: Heterogeneous Spatial-Temporal Graph Transformer for Delivery Time Estimation in Warehouse-Distribution Integration E-Commerce

    Xiaohui Zhao, Shuai Wang, Hai Wang, Tian He, Desheng Zhang, Guang Wang

  84. Geometric Graph Learning for Protein Mutation Effect Prediction

    Kangfei Zhao, Yu Rong, Biaobin Jiang, Jianheng Tang, Hengtong Zhang, Jeffrey Xu Yu, Peilin Zhao

  85. Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs

    Tianyi Zhao, Hui Hu, Lu Cheng

  86. Decentralized Graph Neural Network for Privacy-Preserving Recommendation

    Xiaolin Zheng, Zhongyu Wang, Chaochao Chen, Jiashu Qian, Yao Yang

  87. G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer

    Yuchen Zhuang, Xin Shen, Yan Zhao, Chaosheng Dong, Ming Wang, Jin Li, Chao Zhang

  88. HOVER: Homophilic Oversampling via Edge Removal for Class-Imbalanced Bot Detection on Graphs

    Bradley Ashmore, Lingwei Chen

  89. Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction

    Yuanchen Bei, Hao Chen, Shengyuan Chen, Xiao Huang, Sheng Zhou, Feiran Huang

  90. Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems

    Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda

  91. Self-supervised Learning and Graph Classification under Heterophily

    Yilin Ding, Zhen Liu, Hao Hao

  92. Geometric Matrix Completion via Sylvester Multi-Graph Neural Network

    Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong

  93. KGPR: Knowledge Graph Enhanced Passage Ranking

    Jinyuan Fang, Zaiqiao Meng, Craig Macdonald

  94. Neighborhood Homophily-based Graph Convolutional Network

    Shengbo Gong, Jiajun Zhou, Chenxuan Xie, Qi Xuan

  95. KGrEaT: A Framework to Evaluate Knowledge Graphs via Downstream Tasks

    Nicolas Heist, Sven Hertling, Heiko Paulheim

  96. Stochastic Subgraph Neighborhood Pooling for Subgraph Classification

    Shweta Ann Jacob, Paul Louis, Amirali Salehi-Abari

  97. S-Mixup: Structural Mixup for Graph Neural Networks

    Junghurn Kim, Sukwon Yun, Chanyoung Park

  98. Class Label-aware Graph Anomaly Detection

    Junghoon Kim, Yeonjun In, Kanghoon Yoon, Junmo Lee, Chanyoung Park

  99. Exploring Cohesive Subgraphs in Hypergraphs: The (k,g)-core Approach

    Dahee Kim, Junghoon Kim, Sungsu Lim, Hyun Ji Jeong

  100. Towards Trustworthy Rumor Detection with Interpretable Graph Structural Learning

    Leyuan Liu, Junyi Chen, Zhangtao Cheng, Wenxin Tai, Fan Zhou

  101. Boosting Meta-Learning Cold-Start Recommendation with Graph Neural Network

    Han Liu, Hongxiang Lin, Xiaotong Zhang, Fenglong Ma, Hongyang Chen, Lei Wang, Hong Yu, Xianchao Zhang

  102. STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation

    Shaohua Liu, Yu Qi, Gen Li, Mingjian Chen, Teng Zhang, Jia Cheng, Jun Lei

  103. FairGraph: Automated Graph Debiasing with Gradient Matching

    Yezi Liu

  104. DCGNN: Dual-Channel Graph Neural Network for Social Bot Detection

    Nuoyan Lyu, Bingbing Xu, Fangda Guo, Huawei Shen

  105. Metapath-Guided Data-Augmentation For Knowledge Graphs

    Saurav Manchanda

  106. Learning Visibility Attention Graph Representation for Time Series Forecasting

    Shengzhong Mao, Xiao-Jun Zeng

  107. Graph Contrastive Learning with Graph Info-Min

    En Meng, Yong Liu

  108. Generative Graph Augmentation for Minority Class in Fraud Detection

    Lin Meng, Hesham Mostafa, Marcel Nassar, Xiaonan Zhang, Jiawei Zhang

  109. Efficient Differencing of System-level Provenance Graphs

    Yuta Nakamura, Iyad Kanj, Tanu Malik

  110. VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs

    Mina Samizadeh, Guangmo Tong

  111. Network Embedding with Adaptive Multi-hop Contrast

    Chenhao Wang, Yong Liu, Yan Yang

  112. Training Heterogeneous Graph Neural Networks using Bandit Sampling

    Ta-Yang Wang, Rajgopal Kannan, Viktor Prasanna

  113. Adaptive Graph Neural Diffusion for Traffic Demand Forecasting

    Yiling Wu, Xinfeng Zhang, Yaowei Wang

  114. Geometry Interaction Augmented Graph Collaborative Filtering

    Jie Xu, Chaozhuo Li

  115. Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning

    Tianmeng Yang, Min Zhou, Yujing Wang, Zhengjie Lin, Lujia Pan, Bin Cui, Yunhai Tong

  116. Positive-Unlabeled Node Classification with Structure-aware Graph Learning

    Hansi Yang, Yongqi Zhang, Quanming Yao, James Kwok

  117. Graph-based Alignment and Uniformity for Recommendation

    Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu

  118. BI-GCN: Bilateral Interactive Graph Convolutional Network for Recommendation

    Yinan Zhang, Pei Wang, Congcong Liu, Xiwei Zhao, Hao Qi, Jie He, Junsheng Jin, Changping Peng, Zhangang Lin, Jingping Shao

  119. Knowledge Graph Error Detection with Hierarchical Path Structure

    Zhao Zhang, Fuwei Zhang, Fuzhen Zhuang, Yongjun Xu

  120. Weight Matters: An Empirical Investigation of Distance Oracles on Knowledge Graphs

    Ke Zhang, Jiageng Chen, Zixian Huang, Gong Cheng

  121. LEAD-ID: Language-Enhanced Denoising and Intent Distinguishing Graph Neural Network for Sponsored Search Broad Retrievals

    Xiao Zhou, Ran Wang, Haorui Li, Qiang Liu, Xingxing Wang, Dong Wang

  122. CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs

    Mirela Cazzolato, Saranya Vijayakumar, Meng-Chieh Lee, Catalina Vajiac, Namyong Park, Pedro Fidalgo, Agma J.M. Traina, Christos Faloutsos

  123. Enhancing Catalog Relationship Problems with Heterogeneous Graphs and Graph Neural Networks Distillation

    Boxin Du, Rob Barton, Grant Galloway, Junzhou Huang, Shioulin Sam, Ismail Tutar, Changhe Yuan

  124. FAF: A Risk Detection Framework on Industry-Scale Graphs

    Yice Luo, Guannan Wang, Yongchao Liu, Jiaxin Yue, Weihong Cheng, Binjie Fei

  125. Graph Learning for Exploratory Query Suggestions in an Instant Search System

    Enrico Palumbo, Andreas Damianou, Alice Wang, Alva Liu, Ghazal Fazelnia, Francesco Fabbri, Rui Ferreira, Fabrizio Silvestri, Hugues Bouchard, Claudia Hauff, Mounia Lalmas, Ben Carterette, Praveen Chandar, David Nyhan

  126. GBTTE: Graph Attention Network Based Bus Travel Time Estimation

    Yuecheng Rong, Juntao Yao, Jun Liu, Yifan Fang, Wei Luo, Hao Liu, Jie Ma, Zepeng Dan, Jinzhu Lin, Zhi Wu, Yan Zhang, Chuanming Zhang

  127. GraphFC: Customs Fraud Detection with Label Scarcity

    Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin

  128. Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks

    Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao

  129. Logistics Audience Expansion via Temporal Knowledge Graph

    Hua Yan, Yingqiang Ge, Haotian Wang, Desheng Zhang, Yu Yang

  130. Graph Exploration Matters: Improving both Individual-Level and System-Level Diversity in WeChat Feed Recommendation

    Shuai Yang, Lixin Zhang, Feng Xia, Leyu Lin

  131. Multi-gate Mixture-of-Contrastive-Experts with Graph-based Gating Mechanism for TV Recommendation

    Cong Zhang, Dongyang Liu, Lin Zuo, Junlan Feng, Chao Deng, Jian Sun, Haitao Zeng, Yaohong Zhao

  132. Dual Interests-Aligned Graph Auto-Encoders for Cross-domain Recommendation in WeChat

    Jiawei Zheng, Hao Gu, Chonggang Song, Dandan Lin, Lingling Yi, Chuan Chen

  133. The µ-RA System for Recursive Path Queries over Graphs

    Amela Fejza, Pierre Genevès, Nabil Layaïda, Sarah Chlyah

  134. Investigating Natural and Artificial Dynamics in Graph Data Mining and Machine Learning

    Dongqi Fu

  135. A Neuro-symbolic Approach to Enhance Interpretability of Graph Neural Network through the Integration of External Knowledge

    Kislay Raj

  136. Exploiting Homeostatic Synaptic Modulation in Spiking Neural Networks for Semi-Supervised Graph Learning

    Mingkun Xu

  137. Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges

    Erasmo Purificato, Ludovico Boratto, Ernesto William De Luca

  138. Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings

    Bo Xiong, Mojtaba Nayyeri, Daniel Daza, Michael Cochez

  139. From User Activity Traces to Navigation Graph for Software Enhancement: An Application of Graph Neural Network (GNN) on a Real-World Non-Attributed Graph

    Ikram Boukharouba, Florence Sèdes, Christophe Bortolaso, Florent Mouysset

  140. Astrolabe: Visual Graph Database Queries with Tabular Output

    Michael Miller

  141. Workshop on Enterprise Knowledge Graphs using Large Language Models

    Rajeev Gupta, Srinath Srinivasa

  142. PGB: A PubMed Graph Benchmark for Heterogeneous Network Representation Learning

    Eric W. Lee, Joyce C. Ho

  143. Datasets and Interfaces for Benchmarking Heterogeneous Graph Neural Networks

    Yijian Liu, Hongyi Zhang, Cheng Yang, Ao Li, Yugang Ji, Luhao Zhang, Tao Li, Jinyu Yang, Tianyu Zhao, Juan Yang, Hai Huang, Chuan Shi

  144. OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning

    Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng

AAAI-2023

  1. Self-Supervised Graph Learning for Long-Tailed Cognitive Diagnosis

    Shanshan Wang, Zhen Zeng, Xun Yang, Xingyi Zhang

  2. Exposing the Self-Supervised Space-Time Correspondence Learning via Graph Kernels

    Zheyun Qin, Xiankai Lu, Xiushan Nie, Yilong Yin, Jianbing Shen

  3. Asynchronous Event Processing with Local-Shift Graph Convolutional Network

    Linhui Sun, Yifan Zhang, Jian Cheng, Hanqing Lu

  4. Multi-Modal Knowledge Hypergraph for Diverse Image Retrieval

    Yawen Zeng, Qin Jin, Tengfei Bao, Wenfeng Li

  5. MulGT: Multi-Task Graph-Transformer with Task-Aware Knowledge Injection and Domain Knowledge-Driven Pooling for Whole Slide Image Analysis

    Weiqin Zhao, Shujun Wang, Maximus Yeung, Tianye Niu, Lequan Yu

  6. Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs

    Erel Cohen, Omer Lev, Roie Zivan

  7. Enhanced Multi-Relationships Integration Graph Convolutional Network for Inferring Substitutable and Complementary Items

    Huajie Chen, Jiyuan He, Weisheng Xu, Tao Feng, Ming Liu, Tianyu Song, Runfeng Yao, Yuanyuan Qiao

  8. Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding

    Mingyang Chen, Wen Zhang, Zhen Yao, Yushan Zhu, Yang Gao, Jeff Z. Pan, Huajun Chen

  9. Dual Low-Rank Graph Autoencoder for Semantic and Topological Networks

    Zhaoliang Chen, Zhihao Wu, Shiping Wang, Wenzhong Guo

  10. Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction

    Chanyoung Chung, Joyce Jiyoung Whang

  11. Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs

    Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu

  12. DropMessage: Unifying Random Dropping for Graph Neural Networks

    Taoran Fang, Zhiqing Xiao, Chunping Wang, Jiarong Xu, Xuan Yang, Yang Yang

  13. MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning

    Xumeng Gong, Cheng Yang, Chuan Shi

  14. Generic and Dynamic Graph Representation Learning for Crowd Flow Modeling

    Liangzhe Han, Ruixing Zhang, Leilei Sun, Bowen Du, Yanjie Fu, Tongyu Zhu

  15. Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation

    Han Huang, Leilei Sun, Bowen Du, Weifeng Lv

  16. T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation

    Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu

  17. Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning

    Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye

  18. GLCC: A General Framework for Graph-Level Clustering

    Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang

  19. Signed Laplacian Graph Neural Networks

    Yu Li, Meng Qu, Jian Tang, Yi Chang

  20. Scalable and Effective Conductance-Based Graph Clustering

    Longlong Lin, Ronghua Li, Tao Jia

  21. Multi-Domain Generalized Graph Meta Learning

    Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Guohao Li, Sanglu Lu

  22. IterDE: An Iterative Knowledge Distillation Framework for Knowledge Graph Embeddings

    Jiajun Liu, Peng Wang, Ziyu Shang, Chenxiao Wu

  23. Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating

    Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent CS Lee, Shirui Pan

  24. On Generalized Degree Fairness in Graph Neural Networks

    Zemin Liu, Trung-Kien Nguyen, Yuan Fang

  25. Graph Structure Learning on User Mobility Data for Social Relationship Inference

    Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong

  26. Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces

    Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu

  27. Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information

    Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu

  28. Easy Begun Is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout

    Hongjun Wang, Jiyuan Chen, Tong Pan, Zipei Fan, Xuan Song, Renhe Jiang, Lingyu Zhang, Yi Xie, Zhongyi Wang, Boyuan Zhang

  29. Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment

    Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray Buntine, Christopher Leckie

  30. Beyond Graph Convolutional Network: An Interpretable Regularizer-Centered Optimization Framework

    Shiping Wang, Zhihao Wu, Yuhong Chen, Yong Chen

  31. Augmenting Affective Dependency Graph via Iterative Incongruity Graph Learning for Sarcasm Detection

    Xiaobao Wang, Yiqi Dong, Di Jin, Yawen Li, Longbiao Wang, Jianwu Dang

  32. Temporal Knowledge Graph Reasoning with Historical Contrastive Learning

    Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu

  33. Next POI Recommendation with Dynamic Graph and Explicit Dependency

    Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han

  34. Learning to Count Isomorphisms with Graph Neural Networks

    Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang

  35. Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator

    Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang

  36. Deep Graph Structural Infomax

    Wenting Zhao, Gongping Xu, Zhen Cui, Siqiang Luo, Cheng Long, Tong Zhang

  37. A Provable Framework of Learning Graph Embeddings via Summarization

    Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng

  38. GraphSR: A Data Augmentation Algorithm for Imbalanced Node Classification

    Mengting Zhou, Zhiguo Gong

  39. GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM

    Silin Zhou, Jing Li, Hao Wang, Shuo Shang, Peng Han

  40. Heterogeneous Graph Learning for Multi-Modal Medical Data Analysis

    Sein Kim, Namkyeong Lee, Junseok Lee, Dongmin Hyun, Chanyoung Park

  41. GRIP: Graph Representation of Immune Repertoire Using Graph Neural Network and Transformer

    Yongju Lee, Hyunho Lee, Kyoungseob Shin, Sunghoon Kwon

  42. Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs

    Fang Wu, Dragomir Radev, Stan Z. Li

  43. Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction

    Zhankun Xiong, Shichao Liu, Feng Huang, Ziyan Wang, Xuan Liu, Zhongfei Zhang, Wen Zhang

  44. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs

    Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen

  45. DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity Typing

    Haoran Luo, Haihong E, Ling Tan, Gengxian Zhou, Tianyu Yao, Kaiyang Wan

  46. Generalizing Downsampling from Regular Data to Graphs

    Davide Bacciu, Alessio Conte, Francesco Landolfi

  47. Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactions

    Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Toyotaro Suzumura, Manish Singh

  48. FTM: A Frame-Level Timeline Modeling Method for Temporal Graph Representation Learning

    Bowen Cao, Qichen Ye, Weiyuan Xu, Yuexian Zou

  49. Where Will Players Move Next? Dynamic Graphs and Hierarchical Fusion for Movement Forecasting in Badminton

    Kai-Shiang Chang, Wei-Yao Wang, Wen-Chih Peng

  50. Graph Ordering Attention Networks

    Michail Chatzianastasis, Johannes Lutzeyer, George Dasoulas, Michalis Vazirgiannis

  51. Attribute and Structure Preserving Graph Contrastive Learning

    Jialu Chen, Gang Kou

  52. Context-Aware Safe Medication Recommendations with Molecular Graph and DDI Graph Embedding

    Qianyu Chen, Xin Li, Kunnan Geng, Mingzhong Wang

  53. Topological Pooling on Graphs

    Yuzhou Chen, Yulia R. Gel

  54. Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning

    Jiashun Cheng, Man Li, Jia Li, Fugee Tsung

  55. Scalable Spatiotemporal Graph Neural Networks

    Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi

  56. CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials

    Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly

  57. Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning

    Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu

  58. Interpreting Unfairness in Graph Neural Networks via Training Node Attribution

    Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

  59. Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View

    Jingcan Duan, Siwei Wang, Pei Zhang, En Zhu, Jingtao Hu, Hu Jin, Yue Liu, Zhibin Dong

  60. Directed Acyclic Graph Structure Learning from Dynamic Graphs

    Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi

  61. Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees

    Zhongxi Fang, Jianming Huang, Xun Su, Hiroyuki Kasai

  62. Scalable Attributed-Graph Subspace Clustering

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  63. Handling Missing Data via Max-Entropy Regularized Graph Autoencoder

    Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li

  64. Interpolating Graph Pair to Regularize Graph Classification

    Hongyu Guo, Yongyi Mao

  65. Graph Knows Unknowns: Reformulate Zero-Shot Learning as Sample-Level Graph Recognition

    Jingcai Guo, Song Guo, Qihua Zhou, Ziming Liu, Xiaocheng Lu, Fushuo Huo

  66. Self-Supervised Bidirectional Learning for Graph Matching

    Wenqi Guo, Lin Zhang, Shikui Tu, Lei Xu

  67. Boosting Graph Neural Networks via Adaptive Knowledge Distillation

    Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla

  68. Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis

    Thi Kieu Khanh Ho, Narges Armanfard

  69. Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering

    Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He

  70. Multi-View MOOC Quality Evaluation via Information-Aware Graph Representation Learning

    Lu Jiang, Yibin Wang, Jianan Wang, Pengyang Wang, Minghao Yin

  71. Spatio-Temporal Meta-Graph Learning for Traffic Forecasting

    Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura

  72. Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs

    Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu

  73. Local-Global Defense against Unsupervised Adversarial Attacks on Graphs

    Di Jin, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei, Zhen Wang

  74. Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters

    Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee

  75. LoNe Sampler: Graph Node Embeddings by Coordinated Local Neighborhood Sampling

    Konstantin Kutzkov

  76. I’m Me, We’re Us, and I’m Us: Tri-directional Contrastive Learning on Hypergraphs

    Dongjin Lee, Kijung Shin

  77. Time-Aware Random Walk Diffusion to Improve Dynamic Graph Learning

    Jong-whi Lee, Jinhong Jung

  78. Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks

    Chao Li, Hao Xu, Kun He

  79. Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks

    Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng

  80. Restructuring Graph for Higher Homophily via Adaptive Spectral Clustering

    Shouheng Li, Dongwoo Kim, Qing Wang

  81. Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network

    Tong Li, Jiale Deng, Yanyan Shen, Luyu Qiu, Huang Yongxiang, Caleb Chen Cao

  82. Dual Label-Guided Graph Refinement for Multi-View Graph Clustering

    Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He

  83. Hard Sample Aware Network for Contrastive Deep Graph Clustering

    Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen

  84. Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach

    Sérgio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques, José M. F. Moura, Augusto Santos

  85. Boundary Graph Neural Networks for 3D Simulations

    Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

  86. Multiplex Graph Representation Learning via Common and Private Information Mining

    Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu

  87. Inferring Patient Zero on Temporal Networks via Graph Neural Networks

    Xiaolei Ru, Jack Murdoch Moore, Xin-Ya Zhang, Yeting Zeng, Gang Yan

  88. Neighbor Contrastive Learning on Learnable Graph Augmentation

    Xiao Shen, Dewang Sun, Shirui Pan, Xi Zhou, Laurence T. Yang

  89. Federated Learning on Non-IID Graphs via Structural Knowledge Sharing

    Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang

  90. Metric Multi-View Graph Clustering

    Yuze Tan, Yixi Liu, Hongjie Wu, Jiancheng Lv, Shudong Huang

  91. Heterogeneous Graph Masked Autoencoders

    Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla

  92. USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network

    Yifei Wang, Yupan Wang, Zeyu Zhang, Song Yang, Kaiqi Zhao, Jiamou Liu

  93. FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability

    Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang

  94. Non-IID Transfer Learning on Graphs

    Jun Wu, Jingrui He, Elizabeth Ainsworth

  95. Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework

    Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li

  96. Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks

    Yihan Wu, Aleksandar Bojchevski, Heng Huang

  97. GraphPrompt: Graph-Based Prompt Templates for Biomedical Synonym Prediction

    Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang

  98. Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis

    Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Liò

  99. Reinforcement Causal Structure Learning on Order Graph

    Dezhi Yang, Guoxian Yu, Jun Wang, Zhengtian Wu, Maozu Guo

  100. Simple and Efficient Heterogeneous Graph Neural Network

    Xiaocheng Yang, Mingyu Yan, Shirui Pan, Xiaochun Ye, Dongrui Fan

  101. Cluster-Guided Contrastive Graph Clustering Network

    Xihong Yang, Yue Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Qun Zheng, Xinwang Liu, Liming Fang, En Zhu

  102. Lifelong Compression Mixture Model via Knowledge Relationship Graph

    Fei Ye, Adrian G. Bors

  103. Random Walk Conformer: Learning Graph Representation from Long and Short Range

    Pei-Kai Yeh, Hsi-Wen Chen, Ming-Syan Chen

  104. Priori Anchor Labels Supervised Scalable Multi-View Bipartite Graph Clustering

    Jiali You, Zhenwen Ren, Xiaojian You, Haoran Li, Yuancheng Yao

  105. Substructure Aware Graph Neural Networks

    DingYi Zeng, Wanlong Liu, Wenyu Chen, Li Zhou, Malu Zhang, Hong Qu

  106. ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification

    Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li

  107. DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks

    Lei Zhang, Xiaodong Yan, Jianshan He, Ruopeng Li, Wei Chu

  108. Let the Data Choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-View Clustering

    Pei Zhang, Siwei Wang, Liang Li, Changwang Zhang, Xinwang Liu, En Zhu, Zhe Liu, Lu Zhou, Lei Luo

  109. Spectral Feature Augmentation for Graph Contrastive Learning and Beyond

    Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

  110. Dynamic Heterogeneous Graph Attention Neural Architecture Search

    Zeyang Zhang, Ziwei Zhang, Xin Wang, Yijian Qin, Zhou Qin, Wenwu Zhu

  111. Tensorized Incomplete Multi-View Clustering with Intrinsic Graph Completion

    Shuping Zhao, Jie Wen, Lunke Fei, Bob Zhang

  112. Data Imputation with Iterative Graph Reconstruction

    Jiajun Zhong, Ning Gui, Weiwei Ye

  113. Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models

    Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura

  114. Fair Short Paths in Vertex-Colored Graphs

    Matthias Bentert, Leon Kellerhals, Rolf Niedermeier

  115. GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks

    Angelina Brilliantova, Hannah Miller, Ivona Bezáková

  116. Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction

    Bo Li, Wei Ye, Jinglei Zhang, Shikun Zhang

  117. Graph Component Contrastive Learning for Concept Relatedness Estimation

    Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, Irwin King

  118. Improving Interpretability via Explicit Word Interaction Graph Layer

    Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi

  119. Exploring Faithful Rationale for Multi-Hop Fact Verification via Salience-Aware Graph Learning

    Jiasheng Si, Yingjie Zhu, Deyu Zhou

  120. Continual Graph Convolutional Network for Text Classification

    Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding

  121. Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection

    Tao Yang, Jinghao Deng, Xiaojun Quan, Qifan Wang

ICLR-2023

  1. Towards Open Temporal Graph Neural Networks

    Kaituo Feng, Changsheng Li, Xiaolu Zhang, JUN ZHOU

  2. AutoGT: Automated Graph Transformer Architecture Search

    Zizhao Zhang, Xin Wang, Chaoyu Guan, Ziwei Zhang, Haoyang Li, Wenwu Zhu

  3. Rethinking the Expressive Power of GNNs via Graph Biconnectivity

    Bohang Zhang, Shengjie Luo, Liwei Wang, Di He

  4. Graph Neural Networks for Link Prediction with Subgraph Sketching

    Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire

  5. Do We Really Need Complicated Model Architectures For Temporal Networks?

    Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi

  6. Learning on Large-scale Text-attributed Graphs via Variational Inference

    Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang

  7. Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks

    Guangji Bai, Chen Ling, Liang Zhao

  8. Learning Fair Graph Representations via Automated Data Augmentations

    Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou

  9. Spectral Augmentation for Self-Supervised Learning on Graphs

    Lu Lin, Jinghui Chen, Hongning Wang

  10. Serving Graph Compression for Graph Neural Networks

    Si Si, Felix Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar

  11. Effects of Graph Convolutions in Multi-layer Networks

    Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

  12. LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation

    Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren

  13. Relational Attention: Generalizing Transformers for Graph-Structured Tasks

    Cameron Diao, Ricky Loynd

  14. Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

    Yi-Lun Liao, Tess Smidt

  15. Learning rigid dynamics with face interaction graph networks

    Kelsey R Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William F Whitney, Alvaro Sanchez-Gonzalez, Peter Battaglia, Tobias Pfaff

  16. Relational Attention: Generalizing Transformers for Graph-Structured Tasks

    Cameron Diao, Ricky Loynd

  17. Sign and Basis Invariant Networks for Spectral Graph Representation Learning

    Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

  18. ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion

    Aleksandar Pavlović, Emanuel Sallinger

  19. Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla

  20. DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

    Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan

  21. On Representing Linear Programs by Graph Neural Networks

    Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

  22. ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks

    Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin

  23. MeshDiffusion: Score-based Generative 3D Mesh Modeling

    Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu

  24. LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence

    Zhihao Shi, Xize Liang, Jie Wang

  25. Learning Controllable Adaptive Simulation for Multi-resolution Physics

    Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec

  26. Automated Data Augmentations for Graph Classification

    Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

  27. Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization

    Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang

  28. Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective

    Kuan Li, Yang Liu, Xiang Ao, Qing He

  29. Agent-based Graph Neural Networks

    Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer

  30. Characterizing the Influence of Graph Elements

    Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong

  31. Limitless Stability for Graph Convolutional Networks

    Christian Koke

  32. NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs

    Jinsong Chen, Kaiyuan Gao, Gaichao Li, Kun He

  33. Empowering Graph Representation Learning with Test-Time Graph Transformation

    Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah

  34. N-WL: A New Hierarchy of Expressivity for Graph Neural Networks

    Qing Wang, Dillon Ze Chen, Asiri Wijesinghe, Shouheng Li, Muhammad Farhan

  35. Are More Layers Beneficial to Graph Transformers?

    Haiteng Zhao, Shuming Ma, Dongdong Zhang, Zhi-Hong Deng, Furu Wei

  36. Strategic Classification with Graph Neural Networks

    Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld

  37. Robust Graph Dictionary Learning

    Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng, Hui Qian

  38. Specformer: Spectral Graph Neural Networks Meet Transformers

    Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao

  39. DiGress: Discrete Denoising diffusion for graph generation

    Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard

  40. LogicDP: Creating Labels for Graph Data via Inductive Logic Programming

    Yuan Yang, Faramarz Fekri, James Clayton Kerce, Ali Payani

  41. Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning

    Zehao Niu, Mihai Anitescu, Jie Chen

  42. Explaining Temporal Graph Models through an Explorer-Navigator Framework

    Wenwen Xia, Mincai Lai, Caihua Shan, Yao Zhang, Xinnan Dai, Xiang Li, Dongsheng Li

  43. Learning Symbolic Models for Graph-structured Physical Mechanism

    Hongzhi Shi, Jingtao Ding, Yufan Cao, quanming yao, Li Liu, Yong Li

  44. Efficient Model Updates for Approximate Unlearning of Graph-Structured Data

    Eli Chien, Chao Pan, Olgica Milenkovic

  45. Imitating Graph-Based Planning with Goal-Conditioned Policies

    Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin

  46. MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning

    Namyong Park, Ryan A. Rossi, Nesreen Ahmed, Christos Faloutsos

  47. On Compositional Uncertainty Quantification for Seq2seq Graph Parsing

    Zi Lin, Du Phan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang

  48. Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective

    Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang

  49. Grounding Graph Network Simulators using Physical Sensor Observations

    Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann

  50. Graph Contrastive Learning for Skeleton-based Action Recognition

    Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng

  51. A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps

    Kiarash Jamali, Dari Kimanius, Sjors HW Scheres

  52. Energy-based Out-of-Distribution Detection for Graph Neural Networks

    Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan

  53. Rethinking Graph Lottery Tickets: Graph Sparsity Matters

    Bo Hui, Da Yan, Xiaolong Ma, Wei-Shinn Ku

  54. Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems

    Suresh Bishnoi, Ravinder Bhattoo, Jayadeva Jayadeva, Sayan Ranu, N M Anoop Krishnan

  55. Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network

    Seungwoong Ha, Hawoong Jeong

  56. GReTo: Remedying dynamic graph topology-task discordance via target homophily

    Zhengyang Zhou, qihe huang, Gengyu Lin, Kuo Yang, LEI BAI, Yang Wang

  57. Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks

    Cheng Zhang

  58. Unveiling the sampling density in non-uniform geometric graphs

    Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie

  59. Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization

    Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang

  60. Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules

    Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan, Yue Liu, Siyuan Li, Stan Z. Li

  61. Diffusion Models for Causal Discovery via Topological Ordering

    Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris

  62. Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning

    Deyao Zhu, Li Erran Li, Mohamed Elhoseiny

  63. FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

    Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montufar

  64. Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks

    Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu

  65. Revisiting Robustness in Graph Machine Learning

    Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann

  66. Learnable Graph Convolutional Attention Networks

    Adrián Javaloy, Pablo Sanchez Martin, Amit Levi, Isabel Valera

  67. Matching receptor to odorant with protein language and graph neural networks

    Matej Hladiš, Maxence Lalis, Sebastien Fiorucci, Jérémie Topin

  68. Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation

    Kai Xu, Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker, Luke Robinson

  69. A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

    Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova

  70. Fair Attribute Completion on Graph with Missing Attributes

    Dongliang Guo, Zhixuan Chu, Sheng Li

  71. Multimodal Analogical Reasoning over Knowledge Graphs

    Ningyu Zhang, Lei Li, Xiang Chen, Xiaozhuan Liang, Shumin Deng, Huajun Chen

  72. Global Explainability of GNNs via Logic Combination of Learned Concepts

    Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Lio, Andrea Passerini

  73. GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

    Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik

  74. A2Q: Aggregation-Aware Quantization for Graph Neural Networks

    Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng

  75. Graph Domain Adaptation via Theory-Grounded Spectral Regularization

    Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

  76. Learning Hierarchical Protein Representations via Complete 3D Graph Networks

    Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji

  77. Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States

    Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin

  78. Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation

    Yun Young Choi, Sun Woo Park, Youngho Woo, U Jin Choi

  79. A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks

    Xinyi Wu, Zhengdao Chen, William Wei Wang, Ali Jadbabaie

  80. Anti-Symmetric DGN: a stable architecture for Deep Graph Networks

    Alessio Gravina, Davide Bacciu, Claudio Gallicchio

  81. GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks

    Xiaoqi Wang, Han Wei Shen

  82. Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks

    Bowen Jin, Yu Zhang, Yu Meng, Jiawei Han

  83. Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs

    Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron N Musco

  84. Protein Representation Learning via Knowledge Enhanced Primary Structure Reasoning

    Hong-Yu Zhou, Yunxiang Fu, Zhicheng Zhang, Bian Cheng, Yizhou Yu

  85. Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems

    Zhongyuan Zhao, Ananthram Swami, Santiago Segarra

  86. Anisotropic Message Passing: Graph Neural Networks with Directional and Long-Range Interactions

    Moritz Thürlemann, Sereina Riniker

  87. CktGNN: Circuit Graph Neural Network for Electronic Design Automation

    Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang

  88. Confidence-Based Feature Imputation for Graphs with Partially Known Features

    Daeho Um, Jiwoong Park, Seulki Park, Jin young Choi

  89. Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems

    Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves

  90. Neural Compositional Rule Learning for Knowledge Graph Reasoning

    Kewei Cheng, Nesreen Ahmed, Yizhou Sun

  91. DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks

    Wenqian Li, Yinchuan Li, Zhigang Li, Jianye HAO, Yan Pang

  92. On Representing Mixed-Integer Linear Programs by Graph Neural Networks

    Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

  93. UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph

    Jinhao Jiang, Kun Zhou, Xin Zhao, Ji-Rong Wen

  94. Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs

    Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang

  95. AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks

    Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec

  96. Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs

    Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan

  97. Subsampling in Large Graphs Using Ricci Curvature

    Shushan Wu, Huimin Cheng, Jiazhang Cai, Ping Ma, Wenxuan Zhong

  98. Spacetime Representation Learning

    Marc T. Law, James Lucas

  99. Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

    Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji

  100. MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization

    Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah

  101. A Message Passing Perspective on Learning Dynamics of Contrastive Learning

    Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang

  102. A Differential Geometric View and Explainability of GNN on Evolving Graphs

    Yazheng Liu, Xi Zhang, Sihong Xie

  103. Link Prediction with Non-Contrastive Learning

    William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah

  104. Learning to Induce Causal Structure

    Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Theophane Weber, Matthew Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende

  105. Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

    Yunchong Song, Chenghu Zhou, Xinbing Wang, Zhouhan Lin

  106. Logical Message Passing Networks with One-hop Inference on Atomic Formulas

    Zihao Wang, Yangqiu Song, Ginny Wong, Simon See

  107. Fundamental Limits in Formal Verification of Message-Passing Neural Networks

    Marco Sälzer, Martin Lange

  108. Robust Scheduling with GFlowNets

    David W Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan

  109. Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion

    Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo

  110. O-GNN: incorporating ring priors into molecular modeling

    Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

  111. Molecule Generation For Target Protein Binding with Structural Motifs

    ZAIXI ZHANG, Yaosen Min, Shuxin Zheng, Qi Liu

  112. A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming

    Qingyu Han, Linxin Yang, Qian Chen, Xiang Zhou, Dong Zhang, Akang Wang, Ruoyu Sun, Xiaodong Luo

  113. Label Propagation with Weak Supervision

    Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan

  114. ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond

    Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang

  115. Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem

    Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola

  116. On Explaining Neural Network Robustness with Activation Path

    Ziping Jiang

  117. Equivariant Hypergraph Diffusion Neural Operators

    Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li

  118. Interpretable Geometric Deep Learning via Learnable Randomness Injection

    Siqi Miao, Yunan Luo, Mia Liu, Pan Li

  119. Protein Representation Learning by Geometric Structure Pretraining

    Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

  120. Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction

    Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim, Kuk-Jin Yoon

  121. TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs

    Siheng Xiong, Yuan Yang, Faramarz Fekri, James Clayton Kerce

  122. Boosting Causal Discovery via Adaptive Sample Reweighting

    An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua

WSDM-2023

  1. BLADE: Biased Neighborhood Sampling based Graph Neural Network for Directed Graphs

    Srinivas Virinchi, Anoop Saladi

  2. Simplifying Graph-based Collaborative Filtering for Recommendation

    Li He, Xianzhi Wang, Dingxian Wang, Haoyuan Zou, Hongzhi Yin, Guandong Xu

  3. Self-Supervised Group Graph Collaborative Filtering for Group Recommendation

    Kang Li, Chang-Dong Wang, Jian-Huang Lai, Huaqiang Yuan

  4. Minimum Entropy Principle Guided Graph Neural Networks

    Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su

  5. Learning to Distill Graph Neural Networks

    Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin

  6. MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution

    Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, Dongmei Zhang

  7. Global Counterfactual Explainer for Graph Neural Networks

    Zexi Huang, Mert Kosan, Sourav Medya, Sayan Ranu, Ambuj K. Singh

  8. Effective Graph Kernels for Evolving Functional Brain Networks

    Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu

  9. Self-Supervised Graph Structure Refinement for Graph Neural Networks

    Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye

  10. Learning Stance Embeddings from Signed Social Graphs

    John Pougué-Biyong, Akshay Gupta, Aria Haghighi, Ahmed El-Kishky

  11. Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation

    Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren

  12. A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework

    Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang

  13. Simultaneous Linear Multi-view Attributed Graph Representation Learning and Clustering

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  14. Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs

    Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

  15. Self-supervised Graph Representation Learning for Black Market Account Detection

    Zequan Xu, Lianyun Li, Hui Li, Qihang Sun, Shaofeng Hu, Rongrong Ji

  16. GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection

    Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan

  17. Alleviating Structural Distribution Shift in Graph Anomaly Detection

    Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

  18. Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation

    Qingyu Bing, Qiannan Zhu, Zhicheng Dou

  19. DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation

    Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang

  20. VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation

    Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu, Han Xu

  21. Heterogeneous Graph Contrastive Learning for Recommendation

    Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo

  22. SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation

    Boyu Li, Ting Guo, Xingquan Zhu, Qian Li, Yang Wang, Fang Chen

  23. Robust Training of Graph Neural Networks via Noise Governance

    Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, Jian Wu

  24. Cooperative Explanations of Graph Neural Networks

    Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

  25. Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection

    Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

  26. Towards Faithful and Consistent Explanations for Graph Neural Networks

    Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang

  27. Position-Aware Subgraph Neural Networks with Data-Efficient Learning

    Chang Liu, Yuwen Yang, Zhe Xie, Hongtao Lu, Yue Ding

  28. Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution

    Shenggui Tang, Kaixuan Yao, Jianqing Liang, Zhiqiang Wang, Jiye Liang

  29. DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation

    Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang

  30. Inductive Graph Transformer for Delivery Time Estimation

    Xin Zhou, Jinglong Wang, Yong Liu, Xingyu Wu, Zhiqi Shen, Cyril Leung

  31. Search Behavior Prediction: A Hypergraph Perspective

    Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian

  32. Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation

    Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao

  33. Heterogeneous Graph-based Context-aware Document Ranking

    Shuting Wang, Zhicheng Dou, Yutao Zhu

  34. Graph Summarization via Node Grouping: A Spectral Algorithm

    Arpit Merchant, Michael Mathioudakis, Yanhao Wang

  35. Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph

    Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

  36. Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs

    Linhao Luo, Gholamreza Haffari, Shirui Pan

  37. S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking

    Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu

  38. Combining vs. Transferring Knowledge: Investigating Strategies for Improving Demographic Inference in Low Resource Settings

    Yaguang Liu, Lisa Singh

  39. Active Ensemble Learning for Knowledge Graph Error Detection

    Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha, Zihao Zhao

  40. Stochastic Solutions for Dense Subgraph Discovery in Multilayer Networks

    Yasushi Kawase, Atsushi Miyauchi, Hanna Sumita

  41. Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval

    Taiqiang Wu, Xingyu Bai, Weigang Guo, Weijie Liu, Siheng Li, Yujiu Yang

  42. Web of Conferences: A Conference Knowledge Graph

    Shuo Yu, Ciyuan Peng, Chengchuan Xu, Chen Zhang, Feng Xia

  43. Developing and Evaluating Graph Counterfactual Explanation with GRETEL

    Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo

  44. Generalizing Graph Neural Network across Graphs and Time

    Zhihao Wen

  45. Graphs: Privacy and Generation through ML

    Rucha Bhalchandra Joshi

  46. Data-Efficient Graph Learning Meets Ethical Challenges

    Tao Tang

  47. From Classic GNNs to Hyper-GNNs for Detecting Camouflaged Malicious Actors

    Venus Haghighi

  48. Efficient Graph Learning for Anomaly Detection Systems

    Falih Gozi Febrinanto

WWW-2023

  1. GELTOR: A Graph Embedding Method based on Listwise Learning to Rank

    Masoud Reyhani Hamedani, Jin-Su Ryu, Sang-Wook Kim

  2. Graph-less Collaborative Filtering

    Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu

  3. Fair Graph Representation Learning via Diverse Mixture-of-Experts

    Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang

  4. Multi-Aspect Heterogeneous Graph Augmentation

    Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu, Weiqiang Wang

  5. RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks

    Zeyu Zhang, Jiamou Liu, Xianda Zheng, Yifei Wang, Pengqian Han, Yupan Wang, Kaiqi Zhao, Zijian Zhang

  6. Collaboration-Aware Graph Convolutional Network for Recommender Systems

    Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr

  7. Hierarchical Knowledge Graph Learning Enabled Socioeconomic Indicator Prediction in Location-Based Social Network

    Zhilun Zhou, Yu Liu, Jingtao Ding, Depeng Jin, Yong Li

  8. SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

    Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao

  9. Graph Self-supervised Learning with Augmentation-aware Contrastive Learning

    Dong Chen, Xiang Zhao, Wei Wang, Zhen Tan, Weidong Xiao

  10. Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation

    Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng, Haoming Lyu

  11. Unifying and Improving Graph Convolutional Neural Networks with Wavelet Denoising Filters

    Liangtian Wan, Xiaona Li, Huijin Han, Xiaoran Yan, Lu Sun, Zhaolong Ning, Feng Xia

  12. SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds

    Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren

  13. GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

    Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang

  14. An Attentional Multi-scale Co-evolving Model for Dynamic Link Prediction

    Guozhen Zhang, Tian Ye, Depeng Jin, Yong Li

  15. Robust Graph Representation Learning for Local Corruption Recovery

    Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang

  16. Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation

    Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng, Yang Yao

  17. Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification

    Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li

  18. Graph Neural Networks without Propagation

    Liang Yang, Qiuliang Zhang, Runjie Shi, Wenmiao Zhou, Bingxin Niu, Chuan Wang, Xiaochun Cao, Dongxiao He, Zhen Wang, Yuanfang Guo

  19. TIGER: Temporal Interaction Graph Embedding with Restarts

    Yao Zhang, Yun Xiong, Yongxiang Liao, Yiheng Sun, Yucheng Jin, Xuehao Zheng, Yangyong Zhu

  20. Self-Supervised Teaching and Learning of Representations on Graphs

    Liangtian Wan, Zhenqiang Fu, Lu Sun, Xianpeng Wang, Gang Xu, Xiaoran Yan, Feng Xia

  21. SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization

    Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu

  22. Homophily-oriented Heterogeneous Graph Rewiring

    Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang

  23. HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction

    Qijie Bai, Changli Nie, Haiwei Zhang, Dongming Zhao, Xiaojie Yuan

  24. Rethinking Structural Encodings: Adaptive Graph Transformer for Node Classification Task

    Xiaojun Ma, Qin Chen, Yi Wu, Guojie Song, Liang Wang, Bo Zheng

  25. CMINet: a Graph Learning Framework for Content-aware Multi-channel Influence Diffusion

    Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen

  26. Federated Node Classification over Graphs with Latent Link-type Heterogeneity

    Han Xie, Li Xiong, Carl Yang

  27. Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs

    Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li

  28. Semi-Supervised Embedding of Attributed Multiplex Networks

    Ylli Sadikaj, Justus Rass, Yllka Velaj, Claudia Plant

  29. Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification

    Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao

  30. HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer

    Qiheng Mao, Zemin Liu, Chenghao Liu, Jianling Sun

  31. Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs

    Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan

  32. Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning

    Haoran Yang, Hongxu Chen, Sixiao Zhang, Xiangguo Sun, Qian Li, Xiangyu Zhao, Guandong Xu

  33. Minimum Topology Attacks for Graph Neural Networks

    Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du

  34. Multi-head Variational Graph Autoencoder Constrained by Sum-product Networks

    Riting Xia, Yan Zhang, Chunxu Zhang, Xueyan Liu, Bo Yang

  35. GIF: A General Graph Unlearning Strategy via Influence Function

    Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He

  36. INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging

    Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi, Chaochao Chen, Longbiao Chen

  37. Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation

    Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan

  38. Toward Degree Bias in Embedding-Based Knowledge Graph Completion

    Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang

  39. Unlearning Graph Classifiers with Limited Data Resources

    Chao Pan, Eli Chien, Olgica Milenkovic

  40. KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks

    Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu

  41. GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner

    Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, Jie Tang

  42. CogDL: A Comprehensive Library for Graph Deep Learning

    Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Zhongming Yu, Hengrui Zhang, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yuxiao Dong, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang

  43. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation

    Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang

  44. Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model

    Xiaoyu You, Chi Li, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan, Min Yang

  45. Compressed Interaction Graph based Framework for Multi-behavior Recommendation

    Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang

  46. Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation

    Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang, Bo Zheng

  47. Robust Preference-Guided Denoising for Graph based Social Recommendation

    Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li

  48. Multi-Behavior Recommendation with Cascading Graph Convolution Networks

    Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao, Yuxin Peng

  49. Personalized Graph Signal Processing for Collaborative Filtering

    Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu

  50. Dynamically Expandable Graph Convolution for Streaming Recommendation

    Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma

  51. Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systems

    Heesoo Jung, Sangpil Kim, Hogun Park

  52. Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum

    Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

  53. Node-wise Diffusion for Scalable Graph Learning

    Keke Huang, Jing Tang, Juncheng Liu, Renchi Yang, Xiaokui Xiao

  54. CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization

    Zheheng Luo, Qianqian Xie, Sophia Ananiadou

  55. MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding

    Xiaoyu You, Beina Sheng, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Fuli Feng

  56. Curriculum Graph Poisoning

    Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu

  57. TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

    Haozhen Zhang, Le Yu, Xi Xiao, Qing Li, Francesco Mercaldo, Xiapu Luo, Qixu Liu

  58. Unnoticeable Backdoor Attacks on Graph Neural Networks

    Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang

  59. Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding

    Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin

  60. Event Prediction using Case-Based Reasoning over Knowledge Graphs

    Sola Shirai, Debarun Bhattacharjya, Oktie Hassanzadeh

  61. Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning

    Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang

  62. Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graph

    Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, Yong Dou

  63. Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning

    Xiangrong Zhu, Guangyao Li, Wei Hu

  64. Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods

    Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Johannes Hoffart, Manish Singh, Toyotaro Suzumura

  65. Knowledge Graph Question Answering with Ambiguous Query

    Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong

  66. Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment

    Qian Li, Shu Guo, Yangyifei Luo, Cheng Ji, Lihong Wang, Jiawei Sheng, Jianxin Li

  67. Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs

    Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang

  68. Unsupervised Entity Alignment for Temporal Knowledge Graphs

    Xiaoze Liu, Junyang Wu, Tianyi Li, Lu Chen, Yunjun Gao

  69. Hierarchical Self-Attention Embedding for Temporal Knowledge Graph Completion

    Xin Ren, Luyi Bai, Qianwen Xiao, Xiangxi Meng

  70. KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion

    Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo

  71. TRAVERS: A Diversity-Based Dynamic Approach to Iterative Relevance Search over Knowledge Graphs

    Ziyang Li, Yu Gu, Yulin Shen, Wei Hu, Gong Cheng

  72. Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer

    Wen Zhang, Yushan Zhu, Mingyang Chen, Yuxia Geng, Yufeng Huang, Yajing Xu, Wenting Song, Huajun Chen

  73. TEA: Time-aware Entity Alignment in Knowledge Graphs

    Yu Liu, Wen Hua, Kexuan Xin, Saeid Hosseini, Xiaofang Zhou

  74. Link Prediction with Attention Applied on Multiple Knowledge Graph Embedding Models

    Cosimo Gregucci, Mojtaba Nayyeri, Daniel Hernández, Steffen Staab

  75. Knowledge Graph Completion with Counterfactual Augmentation

    Heng Chang, Jie Cai, Jia Li

  76. Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning

    Ruijie Wang, Zheng Li, Jingfeng Yang, Tianyu Cao, Chao Zhang, Bing Yin, Tarek F. Abdelzaher

  77. Message Function Search for Knowledge Graph Embedding

    Shimin Di, Lei Chen

  78. Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks

    Yue Hu, Yuhang Zhang, Yanbing Wang, Daniel B. Work

  79. Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space

    Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King

  80. Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs

    Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He

  81. PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction

    Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun

  82. Learning to Simulate Crowd Trajectories with Graph Networks

    Hongzhi Shi, Quanming Yao, Yong Li

ICDE-2023

  1. Instant Representation Learning for Recommendation over Large Dynamic Graphs

    Cheng Wu (Tsinghua University); Chaokun Wang (Tsinghua University); Jingcao Xu (Tsinghua University); ZiWei Fang (Tsinghua University); Tiankai Gu (Alibaba Group); Changping Wang (Kuai shou); Yang Song (Kuaishou Inc); Kai Zheng (Kuaishou); Xiaowei Wang (Beijing Kuaishou Technology Co., Ltd.); Guorui Zhou (Kuaishou Inc)*

  2. MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning

    Shangfei Zheng (Soochow University); Weiqing Wang (Monash University); JIanfeng Qu (Soochow University); Hongzhi Yin (The University of Queensland); Wei Chen (Soochow University); Lei Zhao (Soochow University)*

  3. Relational Temporal Graph Convolutional Networks for Ranking-Based Stock Prediction

    Zetao Zheng (University of Electronic Science and Technology of China); Jie Shao (University of Electronic Science and Technology of China); Jia Zhu (Zhejiang Normal University); Heng Tao Shen (University of Electronic Science and Technology of China (UESTC))*

  4. TDB: Breaking All Hop-Constrained Cycles in Billion-Scale Directed Graphs

    You Peng (University of New South Wales); Xuemin Lin (University of New South Wales); Michael R Yu (UNSW); Wenjie Zhang (University of New South Wales); Lu Qin (UTS)*

  5. Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction

    Yufeng Zhang (Soochow University); Weiqing Wang (Monash University); Hongzhi Yin (The University of Queensland); Pengpeng Zhao (Soochow University); Wei Chen (Soochow University); Lei Zhao (Soochow University)*

  6. When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks

    Yuchen Fang (Beijing University of Posts and Telecommunications); Yanjun Qin (Beijing University of Posts and Telecommunications); Haiyong Luo (Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences); Fang Zhao (School of Software Engineering, Beijing University of Posts and Telecommunications); Bingbing Xu ( Institute of Computing Technology,University of Chinese Academy of Sciences); Liang Zeng (Tsinghua University); Chenxing Wang (Beijing University of Posts and Telecommunications)*

  7. Jointly Attacking Graph Neural Network and its Explanations

    “Wenqi FAN (The Hong Kong Polytechnic University); Han Xu (Michigan State University); Wei Jin (Michigan State University); Xiaorui Liu (North Carolina State University); Xianfeng Tang (Amazon); Suhang Wang (Pennsylvania State University); Qing Li (The Hong Kong Polytechnic University); Jiliang Tang (Michigan State University); Jianping Wang (City University of Hong Kong); Charu Aggarwal (IBM)”*

  8. Revisiting Citation Prediction with Cluster-Aware Text-Enhanced Heterogeneous Graph Neural Networks

    Carl Yang (Emory University); Jiawei Han (UIUC)*

  9. CLDG: Contrastive Learning on Dynamic Graphs

    Yiming Xu (Xi’an Jiaotong University); Bin Shi (Xi’an jiaotong University); Teng Ma (Xi’an Jiaotong University); Bo Dong (Xi’an Jiaotong University); Haoyi Zhou (Beihang University); Qinghua Zheng (School of Electronic and Information Engineering, Xi’an Jiaotong University)*

  10. Relational Message Passing for Fully Inductive Knowledge Graph Completion

    Yuxia Geng (Zhejiang University); Jiaoyan Chen (The University of Manchester); Jeff Z. Pan (The University of Edinburgh); Mingyang Chen (Zhejiang University); Song Jiang (Huawei Technologies Co., Ltd); Wen Zhang (Zhejiang University); Huajun Chen (Zhejiang University)*

  11. Layer-refined Graph Convolutional Networks for Recommendation

    Xin Zhou (Nanyang Technological University); Donghui Lin (Okayama University); Yong Liu (Nanyang Technological University); Chunyan Miao (NTU)*

  12. A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation

    Huizi Wu (Shanghai University of Finance and Economics); Hui Fang (Shanghai University of Finance and Economics); Zhu Sun (ASTAR); Cong Geng (Shanghai University of Finance and Economics); Xinyu Kong (Ant Group); Yew Soon Ong (Nanyang Technological University, Nanyang View, Singapore)

  13. HyGNN: Drug-Drug Interaction Prediction via Hypergraph Neural Network

    Khaled Mohammed Saifuddin (Georgia State University); Briana Bumgardner (Rice University); Farhan Tanvir (Oklahoma State University); Esra Akbas (Georgia State University)*

  14. Demystifying Bitcoin Address Behavior via Graph Neural Networks

    Zhengjie Huang (Zhejiang University); Yunyang Huang (UESTC); Peng Qian (Zhejiang University); Jianhai Chen (Zhejiang University); Qinming He (Zhejiang University)*

  15. RETIA: Relation-Entity Twin-Interact Aggregation for Temporal Knowledge Graph Extrapolation

    Kangzheng Liu (Huazhong University of Science and Technology); Feng Zhao (Huazhong University of Science and Technology); Guandong Xu (University of Technology Sydney, Australia); Xianzhi Wang (University of Technology Sydney); Hai Jin (Huazhong University of Science and Technology)*

  16. Air-Ground Spatial Crowdsourcing with UAV Carriers by Geometric Graph Convolutional Multi-Agent Deep Reinforcement Learning

    Yu Wang (Beijing Institute of Technology); Jingfei Wu (Beijing Institute of Technology); Hua Xingyuan (School of Computer Science Beijing Institute of Technology); Chi Harold Liu (Beijing Institute of Technology); Guozheng Li (Beijing Institute of Technology); Jianxin Zhao (Beijing Institute of Technology); Ye Yuan ( Beijing Institute of Technology); Guoren Wang (Beijing Institute of Technology)*

  17. Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting

    Yusheng Zhao (Peking University); Xiao Luo (UCLA); Wei Ju (Peking University); Chong Chen (Peking University); Xian-Sheng Hua (Terminus Group); Ming Zhang (Peking University)*

  18. Disentangled Graph Social Recommendation

    Lianghao Xia (University of Hong Kong); Yizhen Shao (South China University of Technology); Chao Huang (University of Hong Kong); Yong Xu (South China University of Technology); Huance Xu (South China University of Technology); Jian Pei (Simon Fraser University)*

  19. Fast Unsupervised Graph Embedding via Graph Zoom Learning

    Ziyang Liu (Tsinghua University); Chaokun Wang (Tsinghua University); Yunkai Lou (Tsinghua University); Hao Feng (Tsinghua University)*

  20. AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network

    Guanghui Zhu (Nanjing University); zhu zhennan (Nanjing University); Wenjie Wang (Nanjing University); Zhuoer Xu (Nanjing University); Chunfeng Yuan (Nanjing University); Yihua Huang (Nanjing University)*

  21. Multimodal Biological Knowledge Graph Completion via Triple Co-attention Mechanism

    Derong Xu (University of Science and Technology of China); jingbo zhou (Baidu Research); Tong Xu (University of Science and Technology of China); yuan xia (baidu); Ji Liu (Baidu Research); Enhong Chen (University of Science and Technology of China); Dejing Dou (Baidu)*

  22. SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs

    Xiao Qin (AWS AI/ML); Nasrullah Sheikh (IBM); Chuan Lei (Amazon Web Services); Berthold Reinwald (IBM Research-Almaden); Giacomo Domeniconi (U.S. Bank)*

SIGMOD-2023

  1. Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Photovoltaic Data Imputation

    Yangxin Fan (Case Western Reserve University); Xuanji Yu (Case Western Reserve University); Raymond Wieser (Case Western Reserve University); David Meakin (SunPower Corporation); Avishai Shaton (SolarEdge Technologies); Jean-Nicolas Jaubert (CSI Solar Co.Ltd.); Robert Flottemesch (Brookfield Renewable U.S.); Michael Howell (C2 Energy Capital); Jennifer Braid (Sandia National Labs); Laura Bruckman (Case Western Reserve University); Roger H French (Case Western Reserve University); Yinghui Wu (Case Western Reserve University)*

  2. Caerus: A Caching-based Framework for Scalable Temporal Graph Neural Networks

    Yiming Li (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Lei Chen (Hong Kong University of Science and Technology); Mingxuan Yuan (Huawei)*

  3. Scalable and Efficient Full-Graph GNN Training for Large Graphs

    Xinchen Wan (HKUST); Kaiqiang Xu (HKUST); Xudong Liao (HKUST); Yilun Jin (The Hong Kong University of Science and Technology); Kai Chen (HKUST); Xin Jin (Peking University)

  4. EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs

    Haoyang Li (The Hong Kong University of Science and Technology); Lei Chen (Hong Kong University of Science and Technology);

  5. DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU

    Xin Zhang (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Yingxia Shao (BUPT); Lei Chen (Hong Kong University of Science and Technology)

IJCAI-2022

  1. Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network

    Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran

  2. Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors

    Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu

  3. Learning Graph-based Residual Aggregation Network for Group Activity Recognition

    Wei Li, Tianzhao Yang, Xiao Wu, Zhaoquan Yuan

  4. Hypertron: Explicit Social-Temporal Hypergraph Framework for Multi-Agent Forecasting

    Yu Tian, Xingliang Huang, Ruigang Niu, Hongfeng Yu, Peijin Wang, Xian Sun

  5. Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation

    Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen

  6. Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies

    Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar

  7. Hypergraph Structure Learning for Hypergraph Neural Networks

    Derun Cai, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong, Hongyan Li

  8. Entity Alignment with Reliable Path Reasoning and Relation-aware Heterogeneous Graph Transformer

    Weishan Cai, Wenjun Ma, Jieyu Zhan, Yuncheng Jiang

  9. Can Abnormality be Detected by Graph Neural Networks

    Ziwei Chai, Siqi You, Yang Yang, Shiliang Pu, Jiarong Xu, Haoyang Cai, Weihao Jiang

  10. Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

    Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

  11. Filtration-Enhanced Graph Transformation

    Zijian Chen, Rong-Hua Li, Hongchao Qin, Huanzhong Duan, Yanxiong Lu, Qiangqiang Dai, Guoren Wang

  12. Modeling Precursors for Temporal Knowledge Graph Reasoning via Auto-encoder Structure

    Yifu Gao, Linhui Feng, Zhigang Kan, Yi Han, Linbo Qiao, Dongsheng Li

  13. Self-supervised Graph Neural Networks for Multi-behavior Recommendation

    Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao

  14. MERIT: Learning Multi-level Representations on Temporal Graphs

    Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen

  15. GraphDIVE: Graph Classification by Mixture of Diverse Experts

    Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

  16. A Sparse-Motif Ensemble Graph Convolutional Network against Over-smoothing

    Xuan Jiang, Zhiyong Yang, Peisong Wen, Li Su, Qingming Huang

  17. CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning

    Di Jin, Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan

  18. RAW-GNN: RAndom Walk Aggregation based Graph Neural Network

    Di Jin, Rui Wang, Meng Ge, Dongxiao He, Xiang Li, Wei Lin, Weixiong Zhang

  19. Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs

    Hongwei Jin, Xun Chen

  20. TGNN: A Joint Semi-supervised Framework for Graph-level Classification

    Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang

  21. TiRGN: Time-Guided Recurrent Graph Network with Local-Global Historical Patterns for Temporal Knowledge Graph Reasoning

    Yujia Li, Shiliang Sun, Jing Zhao

  22. Raising the Bar in Graph-level Anomaly Detection

    Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

  23. Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention

    Wei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora D. Salim

  24. Beyond Homophily: Structure-aware Path Aggregation Graph Neural Network

    Yifei Sun, Haoran Deng, Yang Yang, Chunping Wang, Jiarong Xu, Renhong Huang, Linfeng Cao, Yang Wang, Lei Chen

  25. Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion

    Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang

  26. Augmenting Knowledge Graphs for Better Link Prediction

    Jiang Wang, Filip Ilievski, Pedro A. Szekely, Ke-Thia Yao

  27. FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs

    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li

  28. Ensemble Multi-Relational Graph Neural Networks

    Yuling Wang, Hao Xu, Yanhua Yu, Mengdi Zhang, Zhenhao Li, Yuji Yang, Wei Wu

  29. Multi-Graph Fusion Networks for Urban Region Embedding

    Shangbin Wu, Xu Yan, Xiaoliang Fan, Shirui Pan, Shichao Zhu, Chuanpan Zheng, Ming Cheng, Cheng Wang

  30. Subgraph Neighboring Relations Infomax for Inductive Link Prediction on Knowledge Graphs

    Xiaohan Xu, Peng Zhang, Yongquan He, Chengpeng Chao, Chaoyang Yan

  31. Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting

    Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li, Yan Huang, Liang Wang, Alex X. Liu

  32. Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction

    Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng, Leilei Sun

  33. GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning

    Weiqi Zhang, Chen Zhang, Fugee Tsung

  34. Enhancing Sequential Recommendation with Graph Contrastive Learning

    Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, Chunyan Miao

  35. Table2Graph: Transforming Tabular Data to Unified Weighted Graph

    Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

  36. Spiking Graph Convolutional Networks

    Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo

  37. Data-Free Adversarial Knowledge Distillation for Graph Neural Networks

    Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun

  38. Proximity Enhanced Graph Neural Networks with Channel Contrast

    Wei Zhuo, Guang Tan

  39. Personalized Federated Learning With a Graph

    Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang

  40. Adversarial Explanations for Knowledge Graph Embeddings

    Patrick Betz, Christian Meilicke, Heiner Stuckenschmidt

  41. Multi-view Unsupervised Graph Representation Learning

    Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu

  42. Bootstrapping Informative Graph Augmentation via A Meta Learning Approach

    Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Fuchun Sun, Changwen Zheng

  43. Attributed Graph Clustering with Dual Redundancy Reduction

    Lei Gong, Sihang Zhou, Wenxuan Tu, Xinwang Liu

  44. Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks

    Minyang Hu, Hong Chang, Bingpeng Ma, Shiguang Shan

  45. Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs

    Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, Jeff Z. Pan

  46. On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration

    Di Jiang, Yuan Cao, Qiang Yang

  47. Graph Masked Autoencoder Enhanced Predictor for Neural Architecture Search

    Kun Jing, Jungang Xu, Pengfei Li

  48. DyGRAIN: An Incremental Learning Framework for Dynamic Graphs

    Seoyoon Kim, Seongjun Yun, Jaewoo Kang

  49. SGAT: Simplicial Graph Attention Network

    See Hian Lee, Feng Ji, Wee Peng Tay

  50. Rethinking the Setting of Semi-supervised Learning on Graphs

    Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang

  51. Deep Graph Matching for Partial Label Learning

    Gengyu Lyu, Yanan Wu, Songhe Feng

  52. Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering

    Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini

  53. RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla

  54. Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla

  55. Initializing Then Refining: A Simple Graph Attribute Imputation Network

    Wenxuan Tu, Sihang Zhou, Xinwang Liu, Yue Liu, Zhiping Cai, En Zhu, Changwang Zhang, Jieren Cheng

  56. EMGC²F: Efficient Multi-view Graph Clustering with Comprehensive Fusion

    Danyang Wu, Jitao Lu, Feiping Nie, Rong Wang, Yuan Yuan

  57. A Simple yet Effective Method for Graph Classification

    Junran Wu, Shangzhe Li, Jianhao Li, Yicheng Pan, Ke Xu

  58. Stabilizing and Enhancing Link Prediction through Deepened Graph Auto-Encoders

    Xinxing Wu, Qiang Cheng

  59. Information Augmentation for Few-shot Node Classification

    Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu

  60. Online ECG Emotion Recognition for Unknown Subjects via Hypergraph-Based Transfer Learning

    Yalan Ye, Tongjie Pan, Qianhe Meng, Jingjing Li, Li Lu

  61. Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport

    Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian

  62. Hierarchical Diffusion Scattering Graph Neural Network

    Ke Zhang, Xinyan Pu, Jiaxing Li, Jiasong Wu, Huazhong Shu, Youyong Kong

  63. RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning

    Yun Zhu, Jianhao Guo, Fei Wu, Siliang Tang

  64. Subsequence-based Graph Routing Network for Capturing Multiple Risk Propagation Processes

    Rui Cheng, Qing Li

  65. Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network

    Alex Mathai, Sambaran Bandyopadhyay, Utkarsh Desai, Srikanth Tamilselvam

  66. Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction

    Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang

  67. FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting

    Xuan Rao, Hao Wang, Liang Zhang, Jing Li, Shuo Shang, Peng Han

  68. Effective Graph Context Representation for Document-level Machine Translation

    Kehai Chen, Muyun Yang, Masao Utiyama, Eiichiro Sumita, Rui Wang, Min Zhang

  69. Interactive Information Extraction by Semantic Information Graph

    Siqi Fan, Yequan Wang, Jing Li, Zheng Zhang, Shuo Shang, Peng Han

  70. Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation

    Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, Yunpeng Li

  71. Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning

    Bowen Xing, Ivor W. Tsang

  72. Contrastive Graph Transformer Network for Personality Detection

    Yangfu Zhu, Linmei Hu, Xinkai Ge, Wanrong Peng, Bin Wu

  73. Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture

    Anoushka Vyas, Sambaran Bandyopadhyay

  74. Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

    Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, Yuan Xie

ICML-2022

  1. Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters

    Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc

  2. Convergence of Invariant Graph Networks

    Chen Cai, Yusu Wang

  3. Structure-Aware Transformer for Graph Representation Learning

    Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt

  4. Faster Fundamental Graph Algorithms via Learned Predictions

    Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang

  5. Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection

    Wenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou

  6. Optimization-Induced Graph Implicit Nonlinear Diffusion

    Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

  7. From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers

    Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten

  8. PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs

    Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen

  9. SE(3) Equivariant Graph Neural Networks with Complete Local Frames

    Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

  10. pathGCN: Learning General Graph Spatial Operators from Paths

    Moshe Eliasof, Eldad Haber, Eran Treister

  11. p-Laplacian Based Graph Neural Networks

    Guoji Fu, Peilin Zhao, Yatao Bian

  12. On the Equivalence Between Temporal and Static Equivariant Graph Representations

    Jianfei Gao, Bruno Ribeiro

  13. Large-Scale Graph Neural Architecture Search

    Chaoyu Guan, Xin Wang, Hong Chen, Ziwei Zhang, Wenwu Zhu

  14. Understanding and Improving Knowledge Graph Embedding for Entity Alignment

    Lingbing Guo, Qiang Zhang, Zequn Sun, Mingyang Chen, Wei Hu, Huajun Chen

  15. G-Mixup: Graph Data Augmentation for Graph Classification

    Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu

  16. GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

    Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu

  17. Going Deeper into Permutation-Sensitive Graph Neural Networks

    Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He

  18. LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation

    David Ireland, Giovanni Montana

  19. Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

    Jaehyeong Jo, Seul Lee, Sung Ju Hwang

  20. Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning

    Hidetaka Kamigaito, Katsuhiko Hayashi

  21. Simultaneous Graph Signal Clustering and Graph Learning

    Abdullah Karaaslanli, Selin Aviyente

  22. DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting

    Shiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, Pyang Li

  23. G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters

    Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin

  24. Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

    Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

  25. Let Invariant Rationale Discovery Inspire Graph Contrastive Learning

    Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua

  26. HousE: Knowledge Graph Embedding with Householder Parameterization

    Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

  27. Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

    Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian

  28. Boosting Graph Structure Learning with Dummy Nodes

    Xin Liu, Jiayang Cheng, Yangqiu Song, Xin Jiang

  29. Local Augmentation for Graph Neural Networks

    Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

  30. SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators

    Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer

  31. Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism

    Siqi Miao, Mia Liu, Pan Li

  32. SpeqNets: Sparsity-aware permutation-equivariant graph networks

    Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh

  33. A Theoretical Comparison of Graph Neural Network Extensions

    Pál András Papp, Roger Wattenhofer

  34. Nonlinear Feature Diffusion on Hypergraphs

    Konstantin Prokopchik, Austin R. Benson, Francesco Tudisco

  35. Graph Neural Architecture Search Under Distribution Shifts

    Yijian Qin, Xin Wang, Ziwei Zhang, Pengtao Xie, Wenwu Zhu

  36. Graph-Coupled Oscillator Networks

    T. Konstantin Rusch, Ben Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein

  37. Rethinking Graph Neural Networks for Anomaly Detection

    Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li

  38. Cross-Space Active Learning on Graph Convolutional Networks

    Yufei Tao, Hao Wu, Shiyuan Deng

  39. What Dense Graph Do You Need for Self-Attention

    Yuxin Wang, Chu-Tak Lee, Qipeng Guo, Zhangyue Yin, Yunhua Zhou, Xuanjing Huang, Xipeng Qiu

  40. How Powerful are Spectral Graph Neural Networks

    Xiyuan Wang, Muhan Zhang

  41. Structural Entropy Guided Graph Hierarchical Pooling

    Junran Wu, Xueyuan Chen, Ke Xu, Shangzhe Li

  42. ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning

    Jun Xia, Lirong Wu, Ge Wang, Jintao Chen, Stan Z. Li

  43. Self-Supervised Representation Learning via Latent Graph Prediction

    Yaochen Xie, Zhao Xu, Shuiwang Ji

  44. Efficient Computation of Higher-Order Subgraph Attribution via Message Passing

    Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima

  45. Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning

    Ling Yang, Shenda Hong

  46. A New Perspective on the Effects of Spectrum in Graph Neural Networks

    Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, Baocai Yin

  47. Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks

    Zhaoning Yu, Hongyang Gao

  48. GraphFM: Improving Large-Scale GNN Training via Feature Momentum

    Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji

  49. Deep and Flexible Graph Neural Architecture Search

    Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang, Bin Cui

  50. NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

    Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui

  51. Learning to Solve PDE-constrained Inverse Problems with Graph Networks

    Qingqing Zhao, David B. Lindell, Gordon Wetzstein

  52. Neural-Symbolic Models for Logical Queries on Knowledge Graphs

    Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang

KDD-2022

  1. Motif Prediction with Graph Neural Networks

    Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler

  2. Efficient Join Order Selection Learning with Graph-based Representation

    Jin Chen, Guanyu Ye, Yan Zhao, Shuncheng Liu, Liwei Deng, Xu Chen, Rui Zhou, Kai Zheng

  3. Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation

    Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King

  4. On Structural Explanation of Bias in Graph Neural Networks

    Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li

  5. FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks

    Kaituo Feng, Changsheng Li, Ye Yuan, Guoren Wang

  6. Meta-Learned Metrics over Multi-Evolution Temporal Graphs

    Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He

  7. Subset Node Anomaly Tracking over Large Dynamic Graphs

    Xingzhi Guo, Baojian Zhou, Steven Skiena

  8. Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction

    Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong

  9. Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation

    Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu

  10. GraphMAE: Self-Supervised Masked Graph Autoencoders

    Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang

  11. Global Self-Attention as a Replacement for Graph Convolution

    Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian

  12. Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs

    Roshni G. Iyer, Yunsheng Bai, Wei Wang, Yizhou Sun

  13. Detecting Cash-out Users via Dense Subgraphs

    Yingsheng Ji, Zheng Zhang, Xinlei Tang, Jiachen Shen, Xi Zhang, Guangwen Yang

  14. A Spectral Representation of Networks: The Path of Subgraphs

    Shengmin Jin, Hao Tian, Jiayu Li, Reza Zafarani

  15. Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

    Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang

  16. Condensing Graphs via One-Step Gradient Matching

    Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin

  17. JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks

    Jian Kang, Qinghai Zhou, Hanghang Tong

  18. CoRGi: Content-Rich Graph Neural Networks with Attention

    Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis

  19. FlowGEN: A Generative Model for Flow Graphs

    Furkan Kocayusufoglu, Arlei Silva, Ambuj K. Singh

  20. Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation

    Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan

  21. KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction

    Han Li, Dan Zhao, Jianyang Zeng

  22. Domain Adaptation in Physical Systems via Graph Kernel

    Haoran Li, Hanghang Tong, Yang Weng

  23. Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning

    Rongfan Li, Ting Zhong, Xinke Jiang, Goce Trajcevski, Jin Wu, Fan Zhou

  24. Graph Structural Attack by Perturbing Spectral Distance

    Lu Lin, Ethan Blaser, Hongning Wang

  25. Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems

    Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao

  26. User-Event Graph Embedding Learning for Context-Aware Recommendation

    Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan, Zhong Ming

  27. Graph-in-Graph Network for Automatic Gene Ontology Description Generation

    Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Adelaide Woicik, Sheng Wang

  28. Joint Knowledge Graph Completion and Question Answering

    Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong

  29. RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams

    Qu Liu, Tingjian Ge

  30. Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries

    Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang

  31. UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs

    Yang Liu, Xiang Ao, Fuli Feng, Qing He

  32. Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation

    Bin Lu, Xiaoying Gan, Lina Yang, Weinan Zhang, Luoyi Fu, Xinbing Wang

  33. Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer

    Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang

  34. Learning Causal Effects on Hypergraphs

    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan

  35. Evaluating Knowledge Graph Accuracy Powered by Optimized Human-machine Collaboration

    Yifan Qi, Weiguo Zheng, Liang Hong, Lei Zou

  36. Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning

    Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

  37. Graph-Flashback Network for Next Location Recommendation

    Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han

  38. SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

    Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans

  39. Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

    Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu

  40. GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks

    Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li

  41. Learning on Graphs with Out-of-Distribution Nodes

    Yu Song, Donglin Wang

  42. Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification

    Zixing Song, Yifei Zhang, Irwin King

  43. Causal Attention for Interpretable and Generalizable Graph Classification

    Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua

  44. GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks

    Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang

  45. Streaming Graph Neural Networks with Generative Replay

    Junshan Wang, Wenhao Zhu, Guojie Song, Liang Wang

  46. Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage

    Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr

  47. Graph Neural Networks with Node-wise Architecture

    Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding

  48. Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction

    Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

  49. Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation

    Zhebin Wu, Lin Shu, Ziyue Xu, Yaomin Chang, Chuan Chen, Zibin Zheng

  50. Self-Supervised Hypergraph Transformer for Recommender Systems

    Lianghao Xia, Chao Huang, Chuxu Zhang

  51. Ultrahyperbolic Knowledge Graph Embeddings

    Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab

  52. Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach

    Ge Yan, Yehui Tang, Junchi Yan

  53. Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation

    Chen-Hsu Yang, Chih-Ya Shen

  54. Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li

  55. TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation

    Di Yao, Haonan Hu, Lun Du, Gao Cong, Shi Han, Jingping Bi

  56. Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

    Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong

  57. Accurate Node Feature Estimation with Structured Variational Graph Autoencoder

    Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, U Kang

  58. ROLAND: Graph Learning Framework for Dynamic Graphs

    Jiaxuan You, Tianyu Du, Jure Leskovec

  59. Multiplex Heterogeneous Graph Convolutional Network

    Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong

  60. Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification

    Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai

  61. Variational Graph Author Topic Modeling

    Delvin Ce Zhang, Hady Wirawan Lauw

  62. Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer

    Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang

  63. Model Degradation Hinders Deep Graph Neural Networks

    Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui

  64. Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks

    Yanfu Zhang, Shangqian Gao, Jian Pei, Heng Huang

  65. COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning

    Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

  66. Instant Graph Neural Networks for Dynamic Graphs

    Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang

  67. How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications

    Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra

  68. Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding

    Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu

  69. Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks

    Wendong Bi, Bingbing Xu, Xiaoqian Sun, Zidong Wang, Huawei Shen, Xueqi Cheng

  70. BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning

    Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, Carl Yang

  71. Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks

    Shengyu Chen, Jacob A. Zwart, Xiaowei Jia

  72. AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks

    Tianyi Chen, Charalampos E. Tsourakakis

  73. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning

    Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong

  74. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning

    Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong

  75. Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series

    Siho Han, Simon S. Woo

  76. ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps

    Jizhou Huang, Haifeng Wang, Yibo Sun, Yunsheng Shi, Zhengjie Huang, An Zhuo, Shikun Feng

  77. Graph Neural Network Training and Data Tiering

    Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-Mei Hwu

  78. GraphWorld: Fake Graphs Bring Real Insights for GNNs

    John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi

  79. Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads

    Bochen Pang, Chaozhuo Li, Yuming Liu, Jianxun Lian, Jianan Zhao, Hao Sun, Weiwei Deng, Xing Xie, Qi Zhang

  80. Friend Recommendations with Self-Rescaling Graph Neural Networks

    Xiran Song, Jianxun Lian, Hong Huang, Mingqi Wu, Hai Jin, Xing Xie

  81. A Graph Learning Based Framework for Billion-Scale Offline User Identification

    Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou

  82. FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning

    Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou

  83. Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks

    Zhiyuan Wang, Fan Zhou, Wenxuan Zeng, Goce Trajcevski, Chunjing Xiao, Yong Wang, Kai Chen

  84. Graph2Route: A Dynamic Spatial-Temporal Graph Neural Network for Pick-up and Delivery Route Prediction

    Haomin Wen, Youfang Lin, Xiaowei Mao, Fan Wu, Yiji Zhao, Haochen Wang, Jianbin Zheng, Lixia Wu, Haoyuan Hu, Huaiyu Wan

  85. Graph Neural Networks for Multimodal Single-Cell Data Integration

    Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang

  86. Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator

    Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec

  87. Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph

    Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang

  88. Graph Attention Multi-Layer Perceptron

    Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui

  89. Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs

    Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis

  90. Dynamic Graph Segmentation for Deep Graph Neural Networks

    Johan Kok Zhi Kang, Suwei Yang, Suriya Venkatesan, Sien Yi Tan, Feng Cheng, Bingsheng He

  91. Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks

    Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao

SIGIR-2022

  1. Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

    Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu

  2. Hypergraph Contrastive Collaborative Filtering

    Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy X. Huang

  3. Graph Trend Filtering Networks for Recommendation

    Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li

  4. Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering

    Changxin Tian, Yuexiang Xie, Yaliang Li, Nan Yang, Wayne Xin Zhao

  5. Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer

    Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao

  6. DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph

    Wenwen Gong, Xuyun Zhang, Yifei Chen, Qiang He, Amin Beheshti, Xiaolong Xu, Chao Yan, Lianyong Qi

  7. Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing

    Hanshuang Tong, Zhen Wang, Yun Zhou, Shiwei Tong, Wenyuan Han, Qi Liu

  8. Few-shot Node Classification on Attributed Networks with Graph Meta-learning

    Yonghao Liu, Mengyu Li, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan

  9. Personalized Fashion Compatibility Modeling via Metapath-guided Heterogeneous Graph Learning

    Weili Guan, Fangkai Jiao, Xuemeng Song, Haokun Wen, Chung-Hsing Yeh, Xiaojun Chang

  10. KETCH: Knowledge Graph Enhanced Thread Recommendation in Healthcare Forums

    Limeng Cui, Dongwon Lee

  11. Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations

    Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras

  12. Co-clustering Interactions via Attentive Hypergraph Neural Network

    Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang

  13. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction

    Qika Lin, Jun Liu, Fangzhi Xu, Yudai Pan, Yifan Zhu, Lingling Zhang, Tianzhe Zhao

  14. Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

    Xiang Chen, Ningyu Zhang, Lei Li, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, Huajun Chen

  15. Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective

    Ying Zhou, Xuanang Chen, Ben He, Zheng Ye, Le Sun

  16. Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding

    Mingyang Chen, Wen Zhang, Yushan Zhu, Hongting Zhou, Zonggang Yuan, Changliang Xu, Huajun Chen

  17. Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning

    Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan, Lingling Zhang

  18. Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation

    Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh, Renrong Weng, Rui Tan

  19. Learning Graph-based Disentangled Representations for Next POI Recommendation

    Zhaobo Wang, Yanmin Zhu, Haobing Liu, Chunyang Wang

  20. Less is More: Reweighting Important Spectral Graph Features for Recommendation

    Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

  21. A Review-aware Graph Contrastive Learning Framework for Recommendation

    Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li

  22. Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation

    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, Quoc Viet Hung Nguyen

  23. Knowledge Graph Contrastive Learning for Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li

  24. Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification

    Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen

  25. An Attribute-Driven Mirror Graph Network for Session-based Recommendation

    Siqi Lai, Erli Meng, Fan Zhang, Chenliang Li, Bin Wang, Aixin Sun

  26. AutoGSR: Neural Architecture Search for Graph-based Session Recommendation

    Jingfan Chen, Guanghui Zhu, Haojun Hou, Chunfeng Yuan, Yihua Huang

  27. Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders

    Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Yuchen Yan, Jinyang Li, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher

  28. Multi-modal Graph Contrastive Learning for Micro-video Recommendation

    Zixuan Yi, Xi Wang, Iadh Ounis, Craig MacDonald

  29. Adversarial Graph Perturbations for Recommendations at Scale

    Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang

  30. Graph Capsule Network with a Dual Adaptive Mechanism

    Xiangping Zheng, Xun Liang, Bo Wu, Yuhui Guo, Xuan Zhang

  31. Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation

    Yinfeng Li, Chen Gao, Hengliang Luo, Depeng Jin, Yong Li

  32. Distilling Knowledge on Text Graph for Social Media Attribute Inference

    Quan Li, Xiaoting Li, Lingwei Chen, Dinghao Wu

  33. DH-HGCN: Dual Homogeneity Hypergraph Convolutional Network for Multiple Social Recommendations

    Jiadi Han, Qian Tao, Yufei Tang, Yuhan Xia

  34. GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment

    Junseok Lee, Yunhak Oh, Yeonjun In, Namkyeong Lee, Dongmin Hyun, Chanyoung Park

  35. GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection

    Xu Chen, Qiu Qiu, Changshan Li, Kunqing Xie

  36. DisenCTR: Dynamic Graph-based Disentangled Representation for Click-Through Rate Prediction

    Yifan Wang, Yifang Qin, Fang Sun, Bo Zhang, Xuyang Hou, Ke Hu, Jia Cheng, Jun Lei, Ming Zhang

  37. An MLP-based Algorithm for Efficient Contrastive Graph Recommendations

    Siwei Liu, Iadh Ounis, Craig Macdonald

  38. Assessing Scientific Research Papers with Knowledge Graphs

    Kexuan Sun, Zhiqiang Qiu, Abel Salinas, Yuzhong Huang, Dong-Ho Lee, Daniel Benjamin, Fred Morstatter, Xiang Ren, Kristina Lerman, Jay Pujara

  39. MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization

    Qianren Mao, Hongdong Zhu, Junnan Liu, Cheng Ji, Hao Peng, Jianxin Li, Lihong Wang, Zheng Wang

  40. LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design

    Haoxin Liu

  41. Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network

    Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi

NeurIPS-2022

  1. Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.

    Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang

  2. Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs.

    Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka

  3. Vision GNN: An Image is Worth Graph of Nodes.

    Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu

  4. Does GNN Pretraining Help Molecular Representation?

    Ruoxi Sun, Hanjun Dai, Adams Wei Yu

  5. ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective.

    Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel

  6. Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs.

    Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein

  7. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.

    Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

  8. MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

  9. NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis.

    Jun Zeng, Mingyang Kou, Hailong Yao

  10. Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding.

    Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao

  11. Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

    Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

  12. A Practical, Progressively-Expressive GNN.

    Lingxiao Zhao, Neil Shah, Leman Akoglu

  13. PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.

    Yasmin Salehi, Dennis Giannacopoulos

  14. NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search.

    Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu

  15. Decoupled Self-supervised Learning for Graphs.

    Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

  16. ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs.

    Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

  17. Revisiting Heterophily For Graph Neural Networks.

    Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup

  18. Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats.

    Hongwei Jin, Zishun Yu, Xinhua Zhang

  19. Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.

    Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

  20. GOOD: A Graph Out-of-Distribution Benchmark.

    Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji

  21. Not too little, not too much: a theoretical analysis of graph (over)smoothing.

    Nicolas Keriven

  22. Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks.

    Ching-Yao Chuang, Stefanie Jegelka

  23. Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum.

    Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei

  24. S3GC: Scalable Self-Supervised Graph Clustering.

    Fnu Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain

  25. Pseudo-Riemannian Graph Convolutional Networks.

    Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab

  26. Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems.

    Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N. M. Anoop Krishnan, Sayan Ranu

  27. Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy.

    Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen

  28. Redundancy-Free Message Passing for Graph Neural Networks.

    Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li

  29. Association Graph Learning for Multi-Task Classification with Category Shifts.

    Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring

  30. EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks.

    Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei

  31. How Powerful are K-hop Message Passing Graph Neural Networks.

    Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

  32. Generalization Analysis of Message Passing Neural Networks on Large Random Graphs.

    Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok

  33. Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture.

    Libin Zhu, Chaoyue Liu, Misha Belkin

  34. A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking.

    Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

  35. Geodesic Graph Neural Network for Efficient Graph Representation Learning.

    Lecheng Kong, Yixin Chen, Muhan Zhang

  36. High-Order Pooling for Graph Neural Networks with Tensor Decomposition.

    Chenqing Hua, Guillaume Rabusseau, Jian Tang

  37. Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift.

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, Wenwu Zhu

  38. GraphQNTK: Quantum Neural Tangent Kernel for Graph Data.

    Yehui Tang, Junchi Yan

  39. On the Robustness of Graph Neural Diffusion to Topology Perturbations.

    Yang Song, Qiyu Kang, Sijie Wang, Kai Zhao, Wee Peng Tay

  40. Few-shot Relational Reasoning via Connection Subgraph Pretraining.

    Qian Huang, Hongyu Ren, Jure Leskovec

  41. Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited.

    Mingguo He, Zhewei Wei, Ji-Rong Wen

  42. Evaluating Graph Generative Models with Contrastively Learned Features.

    Hamed Shirzad, Kaveh Hassani, Danica J. Sutherland

  43. An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries.

    Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon M. Anderson, Henry van den Bedem

  44. Are Defenses for Graph Neural Networks Robust?

    Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski

  45. Equivariant Graph Hierarchy-Based Neural Networks.

    Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

  46. Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination.

    Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu

  47. Template based Graph Neural Network with Optimal Transport Distances.

    Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty

  48. Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks.

    Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

  49. Learning Invariant Graph Representations for Out-of-Distribution Generalization.

    Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu

  50. Task-Agnostic Graph Explanations.

    Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji

  51. A Variational Edge Partition Model for Supervised Graph Representation Learning.

    Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou

  52. CGLB: Benchmark Tasks for Continual Graph Learning.

    Xikun Zhang, Dongjin Song, Dacheng Tao

  53. What Makes Graph Neural Networks Miscalibrated?

    Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers

  54. Analyzing Data-Centric Properties for Graph Contrastive Learning.

    Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan

  55. Learning Bipartite Graphs: Heavy Tails and Multiple Components.

    José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar

  56. Graph Self-supervised Learning with Accurate Discrepancy Learning.

    Dongki Kim, Jinheon Baek, Sung Ju Hwang

  57. Recipe for a General, Powerful, Scalable Graph Transformer.

    Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

  58. Pure Transformers are Powerful Graph Learners.

    Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong

  59. Periodic Graph Transformers for Crystal Material Property Prediction.

    Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji

  60. Co-Modality Graph Contrastive Learning for Imbalanced Node Classification.

    Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

  61. Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning.

    Hyunwook Kang, Taehwan Kwon, Jinkyoo Park, James R. Morrison

  62. Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs.

    Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek F. Abdelzaher

  63. Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering.

    Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang

  64. Neural Topological Ordering for Computation Graphs.

    Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi

  65. Graph Learning Assisted Multi-Objective Integer Programming.

    Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin

  66. Exact Shape Correspondence via 2D graph convolution.

    Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng

  67. SHINE: SubHypergraph Inductive Neural nEtwork.

    Yuan Luo

  68. Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks.

    Yijing Liu, Qinxian Liu, Jian-Wei Zhang, Haozhe Feng, Zhongwei Wang, Zihan Zhou, Wei Chen

  69. Graph Neural Networks with Adaptive Readouts.

    David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò

  70. GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games.

    Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun

  71. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs.

    Ming Jin, Yuan-Fang Li, Shirui Pan

  72. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.

    Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

  73. Versatile Multi-stage Graph Neural Network for Circuit Representation.

    Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao

  74. Contrastive Graph Structure Learning via Information Bottleneck for Recommendation.

    Chunyu Wei, Jian Liang, Di Liu, Fei Wang

  75. Graph Neural Networks are Dynamic Programmers.

    Andrew Joseph Dudzik, Petar Velickovic

  76. Ordered Subgraph Aggregation Networks.

    Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris

  77. Hierarchical Graph Transformer with Adaptive Node Sampling.

    Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

  78. MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

  79. Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.

    Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

  80. Long Range Graph Benchmark.

    Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

  81. GREED: A Neural Framework for Learning Graph Distance Functions.

    Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan T. Chakaravarthy, Yogish Sabharwal, Sayan Ranu

  82. Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank.

    Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

  83. DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection.

    Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis

  84. Contrastive Language-Image Pre-Training with Knowledge Graphs.

    Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang

  85. Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions.

    Masanobu Horie, Naoto Mitsume

  86. Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection.

    Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal

  87. Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure.

    Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang

  88. Non-Linear Coordination Graphs.

    Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang

  89. CLEAR: Generative Counterfactual Explanations on Graphs.

    Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

  90. Learning Physical Dynamics with Subequivariant Graph Neural Networks.

    Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan

  91. BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.

    Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu

  92. Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks.

    Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell

  93. Simplified Graph Convolution with Heterophily.

    Sudhanshu Chanpuriya, Cameron Musco

  94. Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks.

    Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner

  95. Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks.

    Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi

  96. NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification.

    Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan

  97. Parameter-free Dynamic Graph Embedding for Link Prediction.

    Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu

  98. Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias.

    Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

  99. Label-invariant Augmentation for Semi-Supervised Graph Classification.

    Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu

  100. Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks.

    Chenxiao Yang, Qitian Wu, Junchi Yan

  101. Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network.

    Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan

  102. GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs.

    Zenan Li, Qitian Wu, Fan Nie, Junchi Yan

  103. Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders.

    Kiarash Zahirnia, Oliver Schulte, Parmis Nadaf, Ke Li

  104. Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

    Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

  105. Symmetry-induced Disentanglement on Graphs.

    Giangiacomo Mercatali, André Freitas, Vikas Garg

  106. SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks.

    Davide Buffelli, Pietro Lió, Fabio Vandin

  107. Learning to Compare Nodes in Branch and Bound with Graph Neural Networks.

    Abdel Ghani Labassi, Didier Chételat, Andrea Lodi

  108. Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations.

    Ivan Marisca, Andrea Cini, Cesare Alippi

  109. Robust Graph Structure Learning via Multiple Statistical Tests.

    Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin

  110. Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks.

    Indradyumna Roy, Soumen Chakrabarti, Abir De

  111. Provably expressive temporal graph networks.

    Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

  112. Uncovering the Structural Fairness in Graph Contrastive Learning.

    Ruijia Wang, Xiao Wang, Chuan Shi, Le Song

  113. On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs.

    Arjun Subramonian, Kai-Wei Chang, Yizhou Sun

  114. Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.

    Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

  115. Neural Approximation of Graph Topological Features.

    Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

  116. Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective.

    Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li

  117. Graph Neural Network Bandits.

    Parnian Kassraie, Andreas Krause, Ilija Bogunovic

  118. Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains.

    Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia R. Gel, Cuneyt Gurcan Akcora

  119. TwiBot-22: Towards Graph-Based Twitter Bot Detection.

    Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo

  120. Deep Generative Model for Periodic Graphs.

    Shiyu Wang, Xiaojie Guo, Liang Zhao

  121. PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.

    Yasmin Salehi, Dennis Giannacopoulos

  122. Deep Bidirectional Language-Knowledge Graph Pretraining.

    Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec

  123. CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference.

    Ran Ran, Wei Wang, Quan Gang, Jieming Yin, Nuo Xu, Wujie Wen

  124. Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks

    Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf

  125. Graph Reordering for Cache-Efficient Near Neighbor Search.

    Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava

  126. Graph Few-shot Learning with Task-specific Structures.

    Song Wang, Chen Chen, Jundong Li

  127. OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport.

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang

CIKM-2022

  1. KRAF: A Flexible Advertising Framework using Knowledge Graph-Enriched Multi-Agent Reinforcement Learning.

    Jose A. Ayala-Romero, Péter Mernyei, Bichen Shi, Diego Mazón

  2. Memory Graph with Message Rehearsal for Multi-Turn Dialogue Generation.

    Xiaoyu Cai, Yao Fu, Hong Zhao, Weihao Jiang, Shiliang Pu

  3. Towards Self-supervised Learning on Graphs with Heterophily.

    Jingfan Chen, Guanghui Zhu, Yifan Qi, Chunfeng Yuan, Yihua Huang

  4. GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases.

    Runjin Chen, Tong Li, Yanyan Shen, Luyu Qiu, Kaidi Li, Caleb Chen Cao

  5. Explainable Link Prediction in Knowledge Hypergraphs.

    Zirui Chen, Xin Wang, Chenxu Wang, Jianxin Li

  6. Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification.

    Yoonhyuk Choi, Jiho Choi, Taewook Ko, Hyungho Byun, Chong-Kwon Kim

  7. Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities.

    Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu

  8. Higher-order Clustering and Pooling for Graph Neural Networks.

    Alexandre Duval, Fragkiskos D. Malliaros

  9. MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio.

    Jinjia Feng, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei, Hongteng Xu

  10. GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search.

    Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Qinghua Zheng, Jun Zhou, Minnan Luo

  11. Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction.

    Hao Geng, Deqing Wang, Fuzhen Zhuang, Xuehua Ming, Chenguang Du, Ting Jiang, Haolong Guo, Rui Liu

  12. ITSM-GCN: Informative Training Sample Mining for Graph Convolutional Network-based Collaborative Filtering.

    Kaiqi Gong, Xiao Song, Senzhang Wang, Songsong Liu, Yong Li

  13. Evolutionary Preference Learning via Graph Nested GRU ODE for Session-based Recommendation.

    Jiayan Guo, Peiyan Zhang, Chaozhuo Li, Xing Xie, Yan Zhang, Sunghun Kim

  14. Multi-Aggregator Time-Warping Heterogeneous Graph Neural Network for Personalized Micro-Video Recommendation.

    Jinkun Han, Wei Li, Zhipeng Cai, Yingshu Li

  15. Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs.

    Phillip Howard, Arden Ma, Vasudev Lal, Ana Paula Simões, Daniel Korat, Oren Pereg, Moshe Wasserblat, Gadi Singer

  16. Discovering Fine-Grained Semantics in Knowledge Graph Relations.

    Nitisha Jain, Ralf Krestel

  17. Extracting Drug-drug Interactions from Biomedical Texts using Knowledge Graph Embeddings and Multi-focal Loss.

    Xin Jin, Xia Sun, Jiacheng Chen, Richard F. E. Sutcliffe

  18. X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning.

    Baoyu Jing, Shengyu Feng, Yuejia Xiang, Xi Chen, Yu Chen, Hanghang Tong

  19. Contrastive Representation Learning for Conversational Question Answering over Knowledge Graphs.

    Endri Kacupaj, Kuldeep Singh, Maria Maleshkova, Jens Lehmann

  20. SWAG-Net: Semantic Word-Aware Graph Network for Temporal Video Grounding.

    Sunoh Kim, Taegil Ha, Kimin Yun, Jin Young Choi

  21. Relational Self-Supervised Learning on Graphs.

    Namkyeong Lee, Dongmin Hyun, Junseok Lee, Chanyoung Park

  22. Automated Spatio-Temporal Synchronous Modeling with Multiple Graphs for Traffic Prediction.

    Fuxian Li, Huan Yan, Guangyin Jin, Yue Liu, Yong Li, Depeng Jin

  23. MDGCF: Multi-Dependency Graph Collaborative Filtering with Neighborhood- and Homogeneous-level Dependencies.

    Guohui Li, Zhiqiang Guo, Jianjun Li, Chaoyang Wang

  24. Heterogeneous Graph Attention Network for Drug-Target Interaction Prediction.

    Mei Li, Xiangrui Cai, Linyu Li, Sihan Xu, Hua Ji

  25. Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks.

    Yinfeng Li, Chen Gao, Xiaoyi Du, Huazhou Wei, Hengliang Luo, Depeng Jin, Yong Li

  26. Dynamic Network Embedding via Temporal Path Adjacency Matrix Factorization.

    Zhuoming Li, Darong Lai

  27. DA-Net: Distributed Attention Network for Temporal Knowledge Graph Reasoning.

    Kangzheng Liu, Feng Zhao, Hongxu Chen, Yicong Li, Guandong Xu, Hai Jin

  28. Unsupervised Hierarchical Graph Pooling via Substructure-Sensitive Mutual Information Maximization.

    Ning Liu, Songlei Jian, Dongsheng Li, Hongzuo Xu

  29. HeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Traffic.

    Shuncheng Liu, Xu Chen, Ziniu Wu, Liwei Deng, Han Su, Kai Zheng

  30. I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning.

    Yang Liu, Zequn Sun, Guangyao Li, Wei Hu

  31. Social Graph Transformer Networks for Pedestrian Trajectory Prediction in Complex Social Scenarios.

    Yao Liu, Lina Yao, Binghao Li, Xianzhi Wang, Claude Sammut

  32. Are Gradients on Graph Structure Reliable in Gray-box Attacks?

    Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li

  33. HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations.

    Sichun Luo, Xinyi Zhang, Yuanzhang Xiao, Linqi Song

  34. DEMO: Disentangled Molecular Graph Generation via an Invertible Flow Model.

    Changsheng Ma, Qiang Yang, Xin Gao, Xiangliang Zhang

  35. Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting.

    Yihong Ma, Patrick Gérard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla

  36. Adaptive Re-Ranking with a Corpus Graph.

    Sean MacAvaney, Nicola Tonellotto, Craig Macdonald

  37. Automatic Meta-Path Discovery for Effective Graph-Based Recommendation.

    Wentao Ning, Reynold Cheng, Jiajun Shen, Nur Al Hasan Haldar, Ben Kao, Xiao Yan, Nan Huo, Wai Kit Lam, Tian Li, Bo Tang

  38. SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation.

    Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

  39. Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning.

    Yiyue Qian, Yiming Zhang, Nitesh V. Chawla, Yanfang Ye, Chuxu Zhang

  40. Reinforced Continual Learning for Graphs.

    Appan Rakaraddi, Siew-Kei Lam, Mahardhika Pratama, Marcus de Carvalho

  41. From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection.

    Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He

  42. Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction.

    Huinan Sun, Guangliang Yu, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang

  43. A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning.

    Li Sun, Junda Ye, Hao Peng, Philip S. Yu

  44. Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing.

    Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu

  45. Temporality- and Frequency-aware Graph Contrastive Learning for Temporal Network.

    Shiyin Tan, Jingyi You, Dongyuan Li

  46. Interpretable Emotion Analysis Based on Knowledge Graph and OCC Model.

    Shuo Wang, Yifei Zhang, Bochen Lin, Boxun Li

  47. AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training.

    Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang

  48. Imbalanced Graph Classification via Graph-of-Graph Neural Networks.

    Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr

  49. Dynamic Hypergraph Learning for Collaborative Filtering.

    Chunyu Wei, Jian Liang, Bing Bai, Di Liu

  50. Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding.

    Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Jianfeng Qu, Xiaofang Zhou

  51. Taxonomy-Enhanced Graph Neural Networks.

    Lingjun Xu, Shiyin Zhang, Guojie Song, Junshan Wang, Tianshu Wu, Guojun Liu

  52. Semi-supervised Hypergraph Node Classification on Hypergraph Line Expansion.

    Chaoqi Yang, Ruijie Wang, Shuochao Yao, Tarek F. Abdelzaher

  53. GROWN+UP: A "Graph Representation Of a Webpage" Network Utilizing Pre-training.

    Benedict Yeoh, Huijuan Wang

  54. Scalable Graph Sampling on GPUs with Compressed Graph.

    Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui

  55. The Interaction Graph Auto-encoder Network Based on Topology-aware for Transferable Recommendation.

    Ruiyun Yu, Kang Yang, Bingyang Guo

  56. Cognize Yourself: Graph Pre-Training via Core Graph Cognizing and Differentiating.

    Tao Yu, Yao Fu, Linghui Hu, Huizhao Wang, Weihao Jiang, Shiliang Pu

  57. LTE4G: Long-Tail Experts for Graph Neural Networks.

    Sukwon Yun, Kibum Kim, Kanghoon Yoon, Chanyoung Park

  58. Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation.

    Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang

  59. Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion.

    Fuwei Zhang, Zhao Zhang, Xiang Ao, Fuzhen Zhuang, Yongjun Xu, Qing He

  60. Handling RDF Streams: Harmonizing Subgraph Matching, Adaptive Incremental Maintenance, and Matching-free Updates Together.

    Qianzhen Zhang, Deke Guo, Xiang Zhao, Lailong Luo

  61. Contrastive Knowledge Graph Error Detection.

    Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu

  62. A Simple Meta-path-free Framework for Heterogeneous Network Embedding.

    Rui Zhang, Arthur Zimek, Peter Schneider-Kamp

  63. Two-Level Graph Path Reasoning for Conversational Recommendation with User Realistic Preference.

    Rongmei Zhao, Shenggen Ju, Jian Peng, Ning Yang, Fanli Yan, Siyu Sun

  64. MentorGNN: Deriving Curriculum for Pre-Training GNNs.

    Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He

  65. D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation Learning.

    Honglu Zhou, Advith Chegu, Samuel S. Sohn, Zuohui Fu, Gerard de Melo, Mubbasir Kapadia

  66. Decoupled Hyperbolic Graph Attention Network for Modeling Substitutable and Complementary Item Relationships.

    Zhiheng Zhou, Tao Wang, Linfang Hou, Xinyuan Zhou, Mian Ma, Zhuoye Ding

  67. Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation.

    Jun Zhuang, Mohammad Al Hasan

  68. Tiger: Transferable Interest Graph Embedding for Domain-Level Zero-Shot Recommendation.

    Jianhuan Zhuo, Jianxun Lian, Lanling Xu, Ming Gong, Linjun Shou, Daxin Jiang, Xing Xie, Yinliang Yue

  69. Efficient and Effective SPARQL Autocompletion on Very Large Knowledge Graphs.

    Hannah Bast, Johannes Kalmbach, Theresa Klumpp, Florian Kramer, Niklas Schnelle

  70. Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction.

    Roy Benjamin, Uriel Singer, Kira Radinsky

  71. GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction.

    Yi Cao, Sihao Hu, Yu Gong, Zhao Li, Yazheng Yang, Qingwen Liu, Shouling Ji

  72. DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps.

    Jizhou Huang, Zhengjie Huang, Xiaomin Fang, Shikun Feng, Xuyi Chen, Jiaxiang Liu, Haitao Yuan, Haifeng Wang

  73. PlatoGL: Effective and Scalable Deep Graph Learning System for Graph-enhanced Real-Time Recommendation.

    Dandan Lin, Shijie Sun, Jingtao Ding, Xuehan Ke, Hao Gu, Xing Huang, Chonggang Song, Xuri Zhang, Lingling Yi, Jie Wen, Chuan Chen

  74. BRIGHT - Graph Neural Networks in Real-time Fraud Detection.

    Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang

  75. Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction.

    Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang

  76. Graph-based Weakly Supervised Framework for Semantic Relevance Learning in E-commerce.

    Zhiyuan Zeng, Yuzhi Huang, Tianshu Wu, Hongbo Deng, Jian Xu, Bo Zheng

  77. Cross-Domain Product Search with Knowledge Graph.

    Rui Zhu, Yiming Zhao, Wei Qu, Zhongyi Liu, Chenliang Li

  78. Interpretability of BERT Latent Space through Knowledge Graphs.

    Vito Walter Anelli, Giovanni Maria Biancofiore, Alessandro De Bellis, Tommaso Di Noia, Eugenio Di Sciascio

  79. CS-MLGCN: Multiplex Graph Convolutional Networks for Community Search in Multiplex Networks.

    Ali Behrouz, Farnoosh Hashemi

  80. Scalable Graph Representation Learning via Locality-Sensitive Hashing.

    Xiusi Chen, Jyun-Yu Jiang, Wei Wang

  81. On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs.

    Hejie Cui, Zijie Lu, Pan Li, Carl Yang

  82. Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting.

    Aosong Feng, Leandros Tassiulas

  83. Subspace Co-clustering with Two-Way Graph Convolution.

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  84. OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network.

    Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi

  85. AMinerGNN: Heterogeneous Graph Neural Network for Paper Click-through Rate Prediction with Fusion Query.

    Zepeng Huai, Zhe Wang, Yifan Zhu, Peng Zhang

  86. LGP: Few-Shot Class-Evolutionary Learning on Dynamic Graphs.

    Tiancheng Huang, Feng Zhao, Donglin Wang

  87. RealGraphGPU: A High-Performance GPU-Based Graph Engine toward Large-Scale Real-World Network Analysis.

    Myung-Hwan Jang, Yun-Yong Ko, Dongkyu Jeong, Jeong-Min Park, Sang-Wook Kim

  88. GReS: Graphical Cross-domain Recommendation for Supply Chain Platform.

    Zhiwen Jing, Ziliang Zhao, Yang Feng, Xiaochen Ma, Nan Wu, Shengqiao Kang, Cheng Yang, Yujia Zhang, Hao Guo

  89. Commonsense Knowledge Base Completion with Relational Graph Attention Network and Pre-trained Language Model.

    Jinhao Ju, Deqing Yang, Jingping Liu

  90. Models and Benchmarks for Representation Learning of Partially Observed Subgraphs.

    Dongkwan Kim, Jiho Jin, Jaimeen Ahn, Alice Oh

  91. Bootstrapped Knowledge Graph Embedding based on Neighbor Expansion.

    Jun Seon Kim, Seong-Jin Ahn, Myoung Ho Kim

  92. Debiasing Neighbor Aggregation for Graph Neural Network in Recommender Systems.

    Minseok Kim, Jinoh Oh, Jaeyoung Do, Sungjin Lee

  93. Dual-Augment Graph Neural Network for Fraud Detection.

    Qiutong Li, Yanshen He, Cong Xu, Feng Wu, Jianliang Gao, Zhao Li

  94. SmartQuery: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction.

    Xiaoting Li, Yuhang Wu, Vineeth Rakesh, Yusan Lin, Hao Yang, Fei Wang

  95. Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility.

    Yongkang Li, Zipei Fan, Jixiao Zhang, Dengheng Shi, Tianqi Xu, Du Yin, Jinliang Deng, Xuan Song

  96. Embedding Global and Local Influences for Dynamic Graphs.

    Meng Liu, Jiaming Wu, Yong Liu

  97. Memory Augmented Graph Learning Networks for Multivariate Time Series Forecasting.

    Xiangyue Liu, Xinqi Lyu, Xiangchi Zhang, Jianliang Gao, Jiamin Chen

  98. Sampling Enclosing Subgraphs for Link Prediction.

    Paul Louis, Shweta Ann Jacob, Amirali Salehi-Abari

  99. Urban Region Profiling via Multi-Graph Representation Learning.

    Yan Luo, Fu-Lai Chung, Kai Chen

  100. Improving Graph-based Document-Level Relation Extraction Model with Novel Graph Structure.

    Seongsik Park, Dongkeun Yoon, Harksoo Kim

  101. GRETEL: Graph Counterfactual Explanation Evaluation Framework.

    Mario Alfonso Prado-Romero, Giovanni Stilo

  102. Do Graph Neural Networks Build Fair User Models? Assessing Disparate Impact and Mistreatment in Behavioural User Profiling.

    Erasmo Purificato, Ludovico Boratto, Ernesto William De Luca

  103. Explainable Graph-based Fraud Detection via Neural Meta-graph Search.

    Zidi Qin, Yang Liu, Qing He, Xiang Ao

  104. A Model-Centric Explainer for Graph Neural Network based Node Classification.

    Sayan Saha, Monidipa Das, Sanghamitra Bandyopadhyay

  105. A Graph-based Spatiotemporal Model for Energy Markets.

    Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon

  106. ST-GAT: A Spatio-Temporal Graph Attention Network for Accurate Traffic Speed Prediction.

    Junho Song, Jiwon Son, Dong-hyuk Seo, Kyungsik Han, Namhyuk Kim, Sang-Wook Kim

  107. Multi-Aspect Embedding of Dynamic Graphs.

    Aimin Sun, Zhiguo Gong

  108. Leveraging the Graph Structure of Neural Network Training Dynamics.

    Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra

  109. Efficiently Answering Minimum Reachable Label Set Queries in Edge-Labeled Graphs.

    Yanping Wu, Renjie Sun, Chen Chen, Xiaoyang Wang, Xianming Fu

  110. Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty.

    Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li, Zhiqiang Tao

  111. An Enhanced Gated Graph Neural Network for E-commerce Recommendation.

    Jihai Zhang, Fangquan Lin, Cheng Yang, Ziqiang Cui

  112. Graph Representation Learning via Adaptive Multi-layer Neighborhood Diffusion Contrast.

    Jijie Zhang, Yan Yang, Yong Liu, Meng Han, Shaowei Yin

  113. Deep Contrastive Multiview Network Embedding.

    Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang

  114. SuGeR: A Subgraph-based Graph Convolutional Network Method for Bundle Recommendation.

    Zhenning Zhang, Boxin Du, Hanghang Tong

  115. KSG: Knowledge and Skill Graph.

    Feng Zhao, Ziqi Zhang, Donglin Wang

  116. Spherical Graph Embedding for Item Retrieval in Recommendation System.

    Wenqiao Zhu, Yesheng Xu, Xin Huang, Qiyang Min, Xun Zhou

  117. GALGO: Scalable Graph Analytics with a Parallel DBMS.

    Wellington Cabrera, Xiantian Zhou, Ladjel Bellatreche, Carlos Ordonez

  118. DASH: An Agile Knowledge Graph System Disentangling Demands, Algorithms, Data Resources, and Humans.

    Shaowei Chen, Haoran Wang, Jie Liu, Jiahui Wu

  119. A GPU-based Graph Pattern Mining System.

    Lin Hu, Lei Zou

  120. Flurry: A Fast Framework for Provenance Graph Generation for Representation Learning.

    Maya Kapoor, Joshua Melton, Michael Ridenhour, Thomas Moyer, Siddharth Krishnan

  121. Approximate and Interactive Processing of Aggregate Queries on Knowledge Graphs: A Demonstration.

    Yuxiang Wang, Arijit Khan, Xiaoliang Xu, Shuzhan Ye, Shihuang Pan, Yuhan Zhou

  122. gCBO: A Cost-based Optimizer for Graph Databases.

    Linglin Yang, Lei Yang, Yue Pang, Lei Zou

  123. ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics.

    Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou, Ahmet Soylu, Evgeny Kharlamov

  124. ScheRe: Schema Reshaping for Enhancing Knowledge Graph Construction.

    Dongzhuoran Zhou, Baifan Zhou, Zhuoxun Zheng, Ahmet Soylu, Ognjen Savkovic, Egor V. Kostylev, Evgeny Kharlamov

  125. Fifty Shades of Pink: Understanding Color in e-commerce using Knowledge Graphs.

    Lizzie Liang, Sneha Kamath, Petar Ristoski, Qunzhi Zhou, Zhe Wu

  126. Shoe Size Resolution in Search Queries and Product Listings using Knowledge Graphs.

    Petar Ristoski, Aritra Mandal, Simon Becker, Anu Mandalam, Ethan Hart, Sanjika Hewavitharana, Zhe Wu, Qunzhi Zhou

  127. Geographical Address Models in the Indian e-Commerce.

    Ravindra Babu Tallamraju

  128. Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch.

    Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou, Ahmet Soylu, Evgeny Kharlamov

  129. Causal Relationship over Knowledge Graphs.

    Hao Huang

  130. Graph-based Management and Mining of Blockchain Data.

    Arijit Khan, Cuneyt Gurcan Akcora

  131. Mining of Real-world Hypergraphs: Patterns, Tools, and Generators.

    Geon Lee, Jaemin Yoo, Kijung Shin

  132. TrustLOG: The First Workshop on Trustworthy Learning on Graphs.

    Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou

  133. The 1st International Workshop on Federated Learning with Graph Data (FedGraph).

    Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr

AAAI-2022

  1. SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds

    Qingdong He, Zhengning Wang, Hao Zeng, Yi Zeng, Yijun Liu

  2. Graph-Based Point Tracker for 3D Object Tracking in Point Clouds

    Minseong Park, Hongje Seong, Wonje Jang, Euntai Kim

  3. Learning to Detect 3D Facial Landmarks via Heatmap Regression with Graph Convolutional Network

    Yuan Wang, Min Cao, Zhenfeng Fan, Silong Peng

  4. Adaptive Hypergraph Neural Network for Multi-Person Pose Estimation

    Xixia Xu, Qi Zou, Xue Lin

  5. ACGNet: Action Complement Graph Network for Weakly-Supervised Temporal Action Localization

    Zichen Yang, Jie Qin, Di Huang

  6. Hybrid Graph Neural Networks for Few-Shot Learning

    Tianyuan Yu, Sen He, Yi-Zhe Song, Tao Xiang

  7. MAGIC: Multimodal relAtional Graph adversarIal inferenCe for Diverse and Unpaired Text-Based Image Captioning

    Wenqiao Zhang, Haochen Shi, Jiannan Guo, Shengyu Zhang, Qingpeng Cai, Juncheng Li, Sihui Luo, Yueting Zhuang

  8. Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations

    Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou

  9. Differentially Describing Groups of Graphs

    Corinna Coupette, Sebastian Dalleiger, Jilles Vreeken

  10. Molecular Contrastive Learning with Chemical Element Knowledge Graph

    *Yin Fang, Qiang Zhang, Haihong Yang, Xiang Zhuang, Shumin Deng, Wen Zhang, Ming Qin, Zhuo Chen, Xi

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Advances on machine learning of graphs, covering the reading list of recent top academic conferences.

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