| Towards Domain-Agnostic Contrastive Learning |
https://arxiv.org/pdf/2011.04419.pdf |
| Contrastive Representation Learning: A Framework and Review |
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9226466 |
| Hard Negative Mixing for Contrastive Learning |
https://arxiv.org/pdf/2010.01028.pdf |
| Contrastive Learning, multi-view redundancy and linear models |
https://arxiv.org/pdf/2008.10150.pdf |
| Building Your Own Latent |
https://arxiv.org/pdf/2006.07733v3.pdf |
| What Should Not Be Contrastive in COntrastive Learning |
https://arxiv.org/pdf/2008.05659.pdf |
| Unsupervised Learning of Visual Features by COntrasting Cluster Assignments |
https://arxiv.org/pdf/2006.09882.pdf |
| Momentum Contrastive Learning for Few-Shot COVID-19 Diagnosis from Chest CT Images |
https://arxiv.org/pdf/2006.13276.pdf |
| Adversarial Self-Supervised COntrastive Learning |
https://arxiv.org/pdf/2006.07589.pdf |
| On Mutual Information in Contrastive Learning for Visual Representations |
https://arxiv.org/pdf/2005.13149.pdf |
| On Mutual Information Maximization for Representation Learning |
https://openreview.net/pdf?id=rkxoh24FPH |
| What makes for good views for Contrastive Learning |
https://arxiv.org/pdf/2005.10243.pdf |
| On the importance of views in unsupervised representation learning |
https://www.mikehwu.com/papers/representation_view.pdf |
| Learning representations by maximizing mutual information across views |
https://papers.nips.cc/paper/2019/file/ddf354219aac374f1d40b7e760ee5bb7-Paper.pdf |
| Learning Deep Representations by Mutual Information Estimation and Maximization |
https://arxiv.org/pdf/1808.06670.pdf |
| Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere |
https://arxiv.org/pdf/2005.10242.pdf |
| Momentum Contrast for Unsupervised Visual Representation Learning |
https://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf |
| Improved Baselines with Momentum Contrastive Learning |
https://arxiv.org/pdf/2003.04297.pdf |
| A Simple Framework for Contrastive Learning of Visual Representations |
https://arxiv.org/pdf/2002.05709.pdf |
| Intriguing Properties of COntrastive Losses |
https://arxiv.org/pdf/2011.02803.pdf |
| A Theoretical Analysis of Contrastive Unsupervised Representation LEarning |
https://arxiv.org/pdf/1902.09229.pdf |
| Representation Learning with Contrastive Predictive Coding |
https://arxiv.org/pdf/1807.03748.pdf |
| Data-efficient image recognition with contrastive predictive coding. |
https://arxiv.org/pdf/1905.09272.pdf |
| Time-Contrastive Networks: Self-Supervised Learning from Video |
https://arxiv.org/pdf/1704.06888.pdf |
| Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA |
https://arxiv.org/pdf/1605.06336.pdf |
| Improved Deep Metric Learning with Multi-class N-pair Loss Objective |
https://proceedings.neurips.cc/paper/2016/file/6b180037abbebea991d8b1232f8a8ca9-Paper.pdf |
| Self-Supervised Representation Learning by Rotation Feature Decoupling |
https://openaccess.thecvf.com/content_CVPR_2019/papers/Feng_Self-Supervised_Representation_Learning_by_Rotation_Feature_Decoupling_CVPR_2019_paper.pdf |
| Noise Contrastive Estimation : A new estimation principle for unnormalized statistical models |
http://proceedings.mlr.press/v9/gutmann10a/gutmann10a.pdf |
| Self-Supervised Learning of Pretext Invariant Representations |
https://openaccess.thecvf.com/content_CVPR_2020/papers/Misra_Self-Supervised_Learning_of_Pretext-Invariant_Representations_CVPR_2020_paper.pdf |
| Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency |
https://arxiv.org/pdf/1809.01812.pdf |
| Dimensionality Reduction by Learning an Invariant Mapping |
http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf |
| Unsupervised Feature Learning via Non-Parametric Instance Discrimination |
https://arxiv.org/pdf/1805.01978.pdf |
| Learning Word Embeddings Efficiently with Noise Contrastive Learning |
https://papers.nips.cc/paper/2013/file/db2b4182156b2f1f817860ac9f409ad7-Paper.pdf |
| ClusterFit: Improving Generalization of Visual Representations |
https://openaccess.thecvf.com/content_CVPR_2020/papers/Yan_ClusterFit_Improving_Generalization_of_Visual_Representations_CVPR_2020_paper.pdf |
| Data-efficient image recognition with contrastive predictive coding |
https://arxiv.org/pdf/1905.09272.pdf |
| Interpretable COntrastive Learning for Networks |
https://arxiv.org/pdf/2005.12419.pdf |
| Local Contrast LEarning |
https://arxiv.org/pdf/1802.03499.pdf |
| Adversarial Contrastive Estimation |
https://arxiv.org/pdf/1805.03642.pdf |
| On Contrastive Learning for Likelihood-free Inference |
https://arxiv.org/pdf/2002.03712.pdf |
| Contrastive Learning for Structured World Models |
https://arxiv.org/pdf/1911.12247.pdf |
| Contrastive Learning for Video Captioning |
|
| Contrastive Learning for Image Captioning |
https://arxiv.org/pdf/1710.02534.pdf |
| Contrastive Representation Distillation |
https://arxiv.org/pdf/1910.10699.pdf |
| Contrastive Multiview COding |
https://arxiv.org/pdf/1906.05849.pdf |
| Online Object Representations with Contrastive Learning |
https://arxiv.org/pdf/1906.04312.pdf |
| Prototypical Contrastive Learning for Unsupervised Representations |
https://arxiv.org/pdf/2005.04966.pdf |
| Supervised Contrastive Learning |
https://arxiv.org/pdf/2004.11362.pdf |
| CURL: Contrastive Unsupervised Representations for Reinforcement LEarning |
https://arxiv.org/pdf/2004.04136.pdf |
| Clustering based Contrastive Learning for Improving Face Representations |
https://arxiv.org/pdf/2004.02195.pdf |
| Contrastive Learning for Image-to-Image Translation |
https://arxiv.org/pdf/2007.15651.pdf |
| Hybrid Discriminative-Generative Training via Contrastive Learning |
https://arxiv.org/pdf/2007.09070.pdf |
| CSI: Novelty Detection via COntrastive Learning on Distributionally Shifted Instances |
https://arxiv.org/pdf/2007.08176.pdf |
| Approximate Nearest Neighbour Negative COntrastive Learning for Dense Text Retrieval |
https://arxiv.org/pdf/2007.00808.pdf |
| Debiased COntrastive Learning |
https://arxiv.org/pdf/2007.00224.pdf |
| DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations |
https://arxiv.org/pdf/2006.03659.pdf |
| Contrastive Variational Autoencoder Enhances Salient Features |
https://arxiv.org/pdf/1902.04601.pdf |
| Contrastive LEarning with Adversarial Examples |
https://arxiv.org/pdf/2010.12050.pdf |
| Graph Contrastive Learning with Augmentations |
https://arxiv.org/pdf/2010.13902.pdf |
| Hard Negative Mixing for Contrastive Learning |
https://arxiv.org/pdf/2010.01028.pdf |
| CONTRASTIVE LEARNING WITH HARD NEGATIVE SAMPLES |
https://openreview.net/pdf?id=CR1XOQ0UTh- |
| Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs By Comparing Image Representations |
https://arxiv.org/pdf/2007.07423.pdf |
| A CRITICAL ANALYSIS OF SELF-SUPERVISION, OR WHAT WE CAN LEARN FROM A SINGLE IMAGE |
https://arxiv.org/pdf/1904.13132.pdf |
| Affinity and Diversity: Quantifying Mechanisms of Data Augmentation |
https://arxiv.org/pdf/2002.08973.pdf |
| Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere |
https://arxiv.org/pdf/2005.10242.pdf |
| Mining on Manifolds: Metric Learning without Labels |
https://arxiv.org/pdf/1803.11095.pdf |
| Rethinking Image Mixture for Unsupervised Visual Representation Learning |
https://arxiv.org/pdf/2003.05438.pdf |
| Manifold Mixup: Better Representations by Interpolating Hidden States |
http://proceedings.mlr.press/v97/verma19a/verma19a.pdf |
| Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning |
https://arxiv.org/pdf/2003.02546.pdf |
| A Theoretical Analysis of Contrastive Unsupervised Representation Learning |
http://proceedings.mlr.press/v97/saunshi19a/saunshi19a.pdf |
| Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction |
https://arxiv.org/pdf/2102.10106.pdf |
| Broaden Your Views for Self-Supervised Video Learning |
https://arxiv.org/pdf/2103.16559.pdf |
| Contrasting Contrastive Self-Supervised Representation Learning Models |
https://arxiv.org/pdf/2103.14005.pdf |
| What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? |
https://arxiv.org/pdf/2106.05961.pdf |
| Understand and Improve Contrastive Learning Methods for Visual Representation: A Review |
https://arxiv.org/pdf/2106.03259.pdf |
| Integrating Auxiliary Information in Self-supervised Learning |
https://arxiv.org/pdf/2106.02869.pdf |
| Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations |
https://arxiv.org/pdf/2106.05967.pdf |
| Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification |
https://arxiv.org/pdf/2106.08808.pdf |
| Learning to See by Looking at Noise |
https://arxiv.org/pdf/2106.05963.pdf |
| Automated Self-Supervised Learning for Graphs |
https://arxiv.org/pdf/2106.05470.pdf |
| Evolving Losses for Unsupervised Video Representation Learning |
https://arxiv.org/pdf/2002.12177.pdf |
| Big Self-Supervised Models are Strong Semi-Supervised Learners |
https://arxiv.org/pdf/2006.10029.pdf |
| An Empirical Study of Training Self-Supervised Vision Transformers |
https://arxiv.org/pdf/2104.02057.pdf |
| Emerging Properties in Self-Supervised Vision Transformers |
https://arxiv.org/pdf/2104.14294.pdf |
| Residual Contrastive Learning for Joint Demosaicking and Denoising |
https://arxiv.org/pdf/2106.10070.pdf |
| ASCNet: Self-supervised Video Representation Learning with Appearance-Speed Consistency |
https://arxiv.org/pdf/2106.02342 |
| You Never Cluster Alone |
https://arxiv.org/pdf/2106.01908 |
| Large-Scale Unsupervised Person Re-Identification with Contrastive Learning |
https://arxiv.org/pdf/2105.07914 |
| When Does Contrastive Visual Representation Learning Work? |
https://arxiv.org/pdf/2105.05837 |
| Self-Supervised Learning from Automatically Separated Sound Scene |
https://arxiv.org/pdf/2105.02132 |
| Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Coding |
https://arxiv.org/pdf/2104.07070 |
| Towards Solving Inefficiency of Self-supervised Representation Learning |
https://arxiv.org/pdf/2104.08760 |
| CoCoNets: Continuous Contrastive 3D Scene Representations |
https://arxiv.org/pdf/2104.03851 |
| ICE: Inter-instance Contrastive Encoding for Unsupervised Person Re-identification |
https://arxiv.org/pdf/2103.16364 |
| Contrastive Domain Adaptation |
https://arxiv.org/pdf/2103.15566 |
| Unsupervised Document Embedding via Contrastive Augmentation |
https://arxiv.org/pdf/2103.14542 |
| Leveraging background augmentations to encourage semantic focus in self-supervised contrastive learning |
https://arxiv.org/pdf/2103.12719 |
| Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization |
https://arxiv.org/pdf/2103.11144 |
| Self-Supervised Classification Network |
https://arxiv.org/pdf/2103.10994 |
| Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation |
https://arxiv.org/pdf/2103.08454 |
| Extending Contrastive Learning to Unsupervised Coreset Selection |
https://arxiv.org/pdf/2103.03574 |
| Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images |
https://arxiv.org/pdf/2103.03423 |
| Contrastive Separative Coding for Self-supervised Representation Learning |
https://arxiv.org/pdf/2103.00816 |
| Bootstrapped Representation Learning on Graphs |
https://arxiv.org/pdf/2102.06514 |
| Negative Data Augmentation |
https://arxiv.org/pdf/2102.05113 |
| DetCo: Unsupervised Contrastive Learning for Object Detection |
https://arxiv.org/pdf/2102.04803 |
| On self-supervised multi-modal representation learning: An application to Alzheimer's disease |
https://arxiv.org/pdf/2012.13619 |
| Information-Preserving Contrastive Learning for Self-Supervised Representations |
https://arxiv.org/pdf/2012.09962 |
| About contrastive unsupervised representation learning for classification and its convergence |
https://arxiv.org/pdf/2012.01064 |
| Self supervised contrastive learning for digital histopathology |
https://arxiv.org/pdf/2011.13971 |
| Time Series Change Point Detection with Self-Supervised Contrastive Predictive Coding |
https://arxiv.org/pdf/2011.14097 |
| Can Temporal Information Help with Contrastive Self-Supervised Learning? |
https://arxiv.org/pdf/2011.13046 |
| Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning |
https://arxiv.org/pdf/2011.11261 |
| Can Semantic Labels Assist Self-Supervised Visual Representation Learning? |
https://arxiv.org/pdf/2011.08621 |
| Unsupervised Contrastive Learning of Sound Event Representations |
https://arxiv.org/pdf/2011.07616 |
| Unsupervised Video Representation Learning by Bidirectional Feature Prediction |
https://arxiv.org/pdf/2011.06037 |
| Unsupervised Learning of Dense Visual Representations |
https://arxiv.org/pdf/2011.05499 |
| Graph Contrastive Learning with Augmentations |
https://arxiv.org/pdf/2010.13902 |
| G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling |
https://arxiv.org/pdf/2009.12007 |
| CAPT: Contrastive Pre-Training for Learning Denoised Sequence Representations |
https://arxiv.org/pdf/2010.06351 |
| Robust Pre-Training by Adversarial Contrastive Learning |
https://arxiv.org/pdf/2010.13337 |
| MS2L: Multi-Task Self-Supervised Learning for Skeleton Based Action Recognition |
https://arxiv.org/pdf/2010.05599 |
| A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection |
https://arxiv.org/pdf/2009.09107 |
| Contrastive learning, multi-view redundancy, and linear models |
https://arxiv.org/pdf/2008.10150 |
| Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination |
https://arxiv.org/pdf/2008.03813 |
| Spatiotemporal Contrastive Video Representation Learning |
https://arxiv.org/pdf/2008.03800 |
| Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation |
https://arxiv.org/pdf/2007.13465 |
| GraphCL: Contrastive Self-Supervised Learning of Graph Representations |
https://arxiv.org/pdf/2007.08025 |
| Unsupervised Image Classification for Deep Representation Learning |
https://arxiv.org/pdf/2006.11480 |
| Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction |
https://arxiv.org/pdf/2006.08558 |
| Self-supervised Learning from a Multi-view Perspective |
https://arxiv.org/pdf/2006.05576 |
| PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition |
https://arxiv.org/pdf/1911.12409 |
| Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping |
https://arxiv.org/pdf/1906.03764 |
| Simple Distillation Baselines for Improving Small Self-supervised Models |
https://arxiv.org/pdf/2106.11304 |
| VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning |
https://arxiv.org/pdf/2106.11250 |
| Can contrastive learning avoid shortcut solutions? |
https://arxiv.org/pdf/2106.11230 |
| Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations |
https://arxiv.org/pdf/2106.11054 |
| SELF-LABELLING VIA SIMULTANEOUS CLUSTERING AND REPRESENTATION LEARNING |
https://arxiv.org/pdf/1911.05371.pdf |
| A CRITICAL ANALYSIS OF SELF-SUPERVISION, OR WHAT WE CAN LEARN FROM A SINGLE IMAGE |
https://arxiv.org/pdf/1904.13132.pdf |
| Video Representation Learning by Recognizing Temporal Transformations |
https://arxiv.org/abs/2007.10730 |
| MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models |
https://arxiv.org/pdf/2010.05352.pdf |
| Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound |
https://arxiv.org/pdf/2008.06607.pdf |
| MST: Masked Self-Supervised Transformer for Visual Representation |
https://arxiv.org/pdf/2106.05656.pdf |
| Robust Identification of Topological Phase Transition by Self-Supervised Machine Learning Approach |
https://arxiv.org/pdf/2106.12791 |
| From Canonical Correlation Analysis to Self-supervised Graph Neural Networks |
https://arxiv.org/pdf/2106.12484 |
| STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning |
https://arxiv.org/pdf/2106.12407 |
| Learning from Pseudo Lesion: A Self-supervised Framework for COVID-19 Diagnosis |
https://arxiv.org/pdf/2106.12313 |
| Deformed2Self: Self-Supervised Denoising for Dynamic Medical Imaging |
https://arxiv.org/pdf/2106.12175 |
| Bootstrap Representation Learning for Segmentation on Medical Volumes and Sequences |
https://arxiv.org/pdf/2106.12153 |
| Unsupervised Object-Level Representation Learning from Scene Images |
https://arxiv.org/pdf/2106.11952 |
| Credal Self-Supervised Learning |
https://arxiv.org/pdf/2106.11853 |
| Improving Ultrasound Tongue Image Reconstruction from Lip Images Using Self-supervised Learning and Attention Mechanism |
https://arxiv.org/pdf/2106.11769 |
| Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack |
https://arxiv.org/pdf/2106.11644 |
| Multi-layered Semantic Representation Network for Multi-label Image Classification |
https://arxiv.org/pdf/2106.11596 |
| Winning the CVPR'2021 Kinetics-GEBD Challenge: Contrastive Learning Approach |
https://arxiv.org/pdf/2106.11549 |
| Simple Distillation Baselines for Improving Small Self-supervised Models |
https://arxiv.org/pdf/2106.11304 |
| TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? |
https://arxiv.org/pdf/2106.11297.pdf |
| VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning |
https://arxiv.org/pdf/2106.11250 |
| Contrastive Multi-Modal Clustering |
https://arxiv.org/pdf/2106.11193 |
| GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction |
https://arxiv.org/pdf/2106.11133 |
| Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations |
https://arxiv.org/pdf/2106.11054 |
| Interventional Video Grounding with Dual Contrastive Learning |
https://arxiv.org/pdf/2106.11013 |
| Unsupervised Deep Learning by Injecting Low-Rank and Sparse Priors |
https://arxiv.org/pdf/2106.10923 |
| Crop-Transform-Paste: Self-Supervised Learning for Visual Tracking |
https://arxiv.org/pdf/2106.10900 |
| Neighborhood Contrastive Learning for Novel Class Discovery |
https://arxiv.org/pdf/2106.10731 |
| Underwater Image Restoration via Contrastive Learning and a Real-world Dataset |
https://arxiv.org/pdf/2106.10718 |
| Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting |
https://arxiv.org/pdf/2106.10137 |
| Investigating the Role of Negatives in Contrastive Representation Learning |
https://arxiv.org/pdf/2106.09943 |
| Novelty Detection via Contrastive Learning with Negative Data Augmentation |
https://arxiv.org/pdf/2106.09958 |
| Efficient Self-supervised Vision Transformers for Representation Learning |
https://arxiv.org/pdf/2106.09785 |
| MoDist: Motion Distillation for Self-supervised Video Representation Learning |
https://arxiv.org/pdf/2106.09703 |
| An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysis |
https://arxiv.org/pdf/2106.09229 |
| Long-Short Temporal Contrastive Learning of Video Transformers |
https://arxiv.org/pdf/2106.09212 |
| Positional Contrastive Learning for Volumetric Medical Image Segmentation |
https://arxiv.org/pdf/2106.09157 |
| SPeCiaL: Self-Supervised Pretraining for Continual Learning |
https://arxiv.org/pdf/2106.09065 |
| Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification |
https://arxiv.org/pdf/2106.08808 |
| Self-supervised GANs with Label Augmentation |
https://arxiv.org/pdf/2106.08601 |
| Self-Supervised Learning with Kernel Dependence Maximization |
https://arxiv.org/pdf/2106.08320 |
| Interpretable Self-supervised Multi-task Learning for COVID-19 Information Retrieval and Extraction |
https://arxiv.org/pdf/2106.08252 |
| Evaluating Modules in Graph Contrastive Learning |
https://arxiv.org/pdf/2106.08171 |
| Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization |
https://arxiv.org/pdf/2106.07916 |
| Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification |
https://arxiv.org/pdf/2106.07846 |
| Graph Contrastive Learning Automated |
https://arxiv.org/pdf/2106.07594 |
| HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units |
https://arxiv.org/pdf/2106.07447 |
| Self-Supervised Metric Learning in Multi-View Data: A Downstream Task Perspective |
https://arxiv.org/pdf/2106.07138 |
| Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective |
https://arxiv.org/pdf/2106.07115 |
| Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images |
https://arxiv.org/pdf/2106.07009 |
| Learning the Imaging Landmarks: Unsupervised Key point Detection in Lung Ultrasound Videos |
https://arxiv.org/pdf/2106.06987 |
| Contrastive Attention for Automatic Chest X-ray Report Generation |
https://arxiv.org/pdf/2106.06965 |
| InfoBehavior: Self-supervised Representation Learning for Ultra-long Behavior Sequence via Hierarchical Grouping |
https://arxiv.org/pdf/2106.06905 |
| Improving weakly supervised sound event detection with self-supervised auxiliary tasks |
https://arxiv.org/pdf/2106.06858 |
| Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation |
https://arxiv.org/pdf/2106.06801 |
| Large-Scale Unsupervised Object Discovery |
https://arxiv.org/pdf/2106.06650 |
| AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation |
https://arxiv.org/pdf/2106.06250 |
| Hybrid Generative-Contrastive Representation Learning |
https://arxiv.org/pdf/2106.06162 |
| Cross-domain Contrastive Learning for Unsupervised Domain Adaptation |
https://arxiv.org/pdf/2106.05528 |
| ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation |
https://arxiv.org/pdf/2106.05095 |
| Self-supervision of Feature Transformation for Further Improving Supervised Learning |
https://arxiv.org/pdf/2106.04922 |
| Self-supervised Feature Enhancement: Applying Internal Pretext Task to Supervised Learning |
https://arxiv.org/pdf/2106.04921 |
| Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style |
https://arxiv.org/pdf/2106.04619 |
| DETReg: Unsupervised Pretraining with Region Priors for Object Detection |
https://arxiv.org/pdf/2106.04550 |
| Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation |
https://arxiv.org/pdf/2106.04195 |
| Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss |
https://arxiv.org/pdf/2106.04156 |
| Self-Supervision & Meta-Learning for One-Shot Unsupervised Cross-Domain Detection |
https://arxiv.org/pdf/2106.03496 |
| Self-supervised Rubik's Cube Solver |
https://arxiv.org/pdf/2106.03157 |
| Self-Damaging Contrastive Learning |
https://arxiv.org/pdf/2106.02990 |
| Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations |
https://arxiv.org/pdf/2106.02866 |
| Self-Supervised Learning of Domain Invariant Features for Depth Estimation |
https://arxiv.org/pdf/2106.02594 |
| Graph Barlow Twins: A self-supervised representation learning framework for graphs |
https://arxiv.org/pdf/2106.02466 |
| Attention-Guided Supervised Contrastive Learning for Semantic Segmentation |
https://arxiv.org/pdf/2106.01596 |
| Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging |
https://arxiv.org/pdf/2106.00919 |
| Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning |
https://arxiv.org/pdf/2105.15134 |
| Unsupervised Action Segmentation with Self-supervised Feature Learning and Co-occurrence Parsing |
https://arxiv.org/pdf/2105.14158 |
| Self-supervised Detransformation Autoencoder for Representation Learning in Open Set Recognition |
https://arxiv.org/pdf/2105.13557 |
| Self-Ensembling Contrastive Learning for Semi-Supervised Medical Image Segmentation |
https://arxiv.org/pdf/2105.12924 |
| Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning |
https://arxiv.org/pdf/2105.12722 |
| Self-Supervised Graph Representation Learning via Topology Transformations |
https://arxiv.org/pdf/2105.11689 |
| Backdoor Attacks on Self-Supervised Learning |
https://arxiv.org/pdf/2105.10123 |
| Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification |
https://arxiv.org/pdf/2105.09684 |
| Heterogeneous Contrastive Learning |
https://arxiv.org/pdf/2105.09401 |
| Balancing Robustness and Sensitivity using Feature Contrastive Learning |
https://arxiv.org/pdf/2105.09394 |
| Self-Supervised Learning for Fine-Grained Visual Categorization |
https://arxiv.org/pdf/2105.08788 |
| Divide and Contrast: Self-supervised Learning from Uncurated Data |
https://arxiv.org/pdf/2105.08054 |
| Unsupervised Deep Learning Methods for Biological Image Reconstruction |
https://arxiv.org/pdf/2105.08040 |
| Large-Scale Unsupervised Person Re-Identification with Contrastive Learning |
https://arxiv.org/pdf/2105.07914 |
| Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification |
https://arxiv.org/pdf/2105.07566 |
| Self-supervised on Graphs: Contrastive, Generative,or Predictive |
https://arxiv.org/pdf/2105.07342 |
| Mean Shift for Self-Supervised Learning |
https://arxiv.org/pdf/2105.07269 |
| Evaluating the Robustness of Self-Supervised Learning in Medical Imaging |
https://arxiv.org/pdf/2105.06986 |
| Using Self-Supervised Co-Training to Improve Facial Representation |
https://arxiv.org/pdf/2105.06421 |
| Electrocardio Panorama: Synthesizing New ECG Views with Self-supervision |
https://arxiv.org/pdf/2105.06293 |
| Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning |
https://arxiv.org/pdf/2105.05682 |
| VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning |
https://arxiv.org/pdf/2105.04906 |
| Self-Supervised Learning with Swin Transformers |
https://arxiv.org/pdf/2105.04553 |
| Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning |
https://arxiv.org/pdf/2105.04532 |
| You Only Learn One Representation: Unified Network for Multiple Tasks |
https://arxiv.org/pdf/2105.04206 |
| Self-supervised spectral matching network for hyperspectral target detection |
https://arxiv.org/pdf/2105.04078 |
| Contrastive Conditional Transport for Representation Learning |
https://arxiv.org/pdf/2105.03746 |
| Contrastive Learning for Unsupervised Image-to-Image Translation |
https://arxiv.org/pdf/2105.03117 |
| Unsupervised Visual Representation Learning by Tracking Patches in Video |
https://arxiv.org/pdf/2105.02545 |
| Contrastive Learning and Self-Training for Unsupervised Domain Adaptation in Semantic Segmentation |
https://arxiv.org/pdf/2105.02001 |
| MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering |
https://arxiv.org/pdf/2105.01899 |
| Representation Learning for Clustering via Building Consensus |
https://arxiv.org/pdf/2105.01289 |
| Self-Supervised Approach for Facial Movement Based Optical Flow |
https://arxiv.org/pdf/2105.01256 |
| On Feature Decorrelation in Self-Supervised Learning |
https://arxiv.org/pdf/2105.00470 |
| CoCon: Cooperative-Contrastive Learning |
https://arxiv.org/pdf/2104.14764 |
| A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning |
https://arxiv.org/pdf/2104.14558 |
| Image Synthesis as a Pretext for Unsupervised Histopathological Diagnosis |
https://arxiv.org/pdf/2104.13797 |
| A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive Learning |
https://arxiv.org/pdf/2104.13712 |
| Shot Contrastive Self-Supervised Learning for Scene Boundary Detection |
https://arxiv.org/pdf/2104.13537 |
| Multimodal Contrastive Training for Visual Representation Learning |
https://arxiv.org/pdf/2104.12836 |
| Multimodal Self-Supervised Learning of General Audio Representations |
https://arxiv.org/pdf/2104.12807 |
| Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos |
https://arxiv.org/pdf/2104.12671 |
| Mutual Contrastive Learning for Visual Representation Learning |
https://arxiv.org/pdf/2104.12565 |
| How Well Self-Supervised Pre-Training Performs with Streaming Data? |
https://arxiv.org/pdf/2104.12081 |
| Aligned Contrastive Predictive Coding |
https://arxiv.org/pdf/2104.11946 |
| DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning |
https://arxiv.org/pdf/2104.11507 |
| Inductive biases and Self Supervised Learning in modelling a physical heating system |
https://arxiv.org/pdf/2104.11478 |
| VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text |
https://arxiv.org/pdf/2104.11178 |
| Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning |
https://arxiv.org/pdf/2104.11056 |
| Self-Supervised Learning from Semantically Imprecise Data |
https://arxiv.org/pdf/2104.10901 |
| Contrastive Learning for Sports Video: Unsupervised Player Classification |
https://arxiv.org/pdf/2104.10068 |
| Fine-grained Anomaly Detection via Multi-task Self-Supervision |
https://arxiv.org/pdf/2104.09993 |
| Distill on the Go: Online knowledge distillation in self-supervised learning |
https://arxiv.org/pdf/2104.09866 |
| SelfReg: Self-supervised Contrastive Regularization for Domain Generalization |
https://arxiv.org/pdf/2104.09841 |
| A Framework using Contrastive Learning for Classification with Noisy Labels |
https://arxiv.org/pdf/2104.09563 |
| DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning |
https://arxiv.org/pdf/2104.09124 |
| Contrastive Learning Improves Model Robustness Under Label Noise |
https://arxiv.org/pdf/2104.08984 |
| Color Variants Identification via Contrastive Self-Supervised Representation Learning |
https://arxiv.org/pdf/2104.08581 |
| Self-supervised Video Retrieval Transformer Network |
https://arxiv.org/pdf/2104.07993 |
| Pareto Self-Supervised Training for Few-Shot Learning |
https://arxiv.org/pdf/2104.07841 |
| Contrastive Learning with Stronger Augmentations |
https://arxiv.org/pdf/2104.07713 |
| Dual Contrastive Learning for Unsupervised Image-to-Image Translation |
https://arxiv.org/pdf/2104.07689 |
| Self-supervised Video Object Segmentation by Motion Grouping |
https://arxiv.org/pdf/2104.07658 |
| Large-Scale Self- and Semi-Supervised Learning for Speech Translation |
https://arxiv.org/pdf/2104.06678 |
| ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration |
https://arxiv.org/pdf/2104.06468 |
| Self-supervised object detection from audio-visual correspondence |
https://arxiv.org/pdf/2104.06401 |
| Understanding Hard Negatives in Noise Contrastive Estimation |
https://arxiv.org/pdf/2104.06245 |
| Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation |
https://arxiv.org/pdf/2104.06087 |
| Unifying domain adaptation and self-supervised learning for CXR segmentation via AdaIN-based knowledge distillation |
https://arxiv.org/pdf/2104.05892 |
| Where and What? Examining Interpretable Disentangled Representations |
https://arxiv.org/pdf/2104.05622 |
| Self-Training with Weak Supervision |
https://arxiv.org/pdf/2104.05514 |
| Saddlepoints in Unsupervised Least Squares |
https://arxiv.org/pdf/2104.05000 |
| Stereo Matching by Self-supervision of Multiscopic Vision |
https://arxiv.org/pdf/2104.04170 |
| Context-self contrastive pretraining for crop type semantic segmentation |
https://arxiv.org/pdf/2104.04310 |
| eGAN: Unsupervised approach to class imbalance using transfer learning |
https://arxiv.org/pdf/2104.04162 |
| SiT: Self-supervised vIsion Transformer |
https://arxiv.org/pdf/2104.03602 |
| Self-Supervised Learning for Semi-Supervised Temporal Action Proposal |
https://arxiv.org/pdf/2104.03214 |
| Utilizing Self-supervised Representations for MOS Prediction |
https://arxiv.org/pdf/2104.03017 |
| Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data |
https://arxiv.org/pdf/2104.02932 |
| Self-Supervised Learning for Gastritis Detection with Gastric X-ray Images |
https://arxiv.org/pdf/2104.02864 |
| Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs |
https://arxiv.org/pdf/2104.02326 |
| Unsupervised Discovery of the Long-Tail in Instance Segmentation Using Hierarchical Self-Supervision |
https://arxiv.org/pdf/2104.01257 |
| Self-supervised Video Representation Learning by Context and Motion Decoupling |
https://arxiv.org/pdf/2104.00862 |
| LatentCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions |
https://arxiv.org/pdf/2104.00820 |
| Composable Augmentation Encoding for Video Representation Learning |
https://arxiv.org/pdf/2104.00616 |
| Jigsaw Clustering for Unsupervised Visual Representation Learning |
https://arxiv.org/pdf/2104.00323 |
| Self-supervised Motion Learning from Static Images |
https://arxiv.org/pdf/2104.00240 |
| Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective |
https://arxiv.org/pdf/2103.17263 |
| On the Origin of Species of Self-Supervised Learning |
https://arxiv.org/pdf/2103.17143 |
| MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption |
https://arxiv.org/pdf/2103.16201 |
| Self-supervised Image-text Pre-training With Mixed Data In Chest X-rays |
https://arxiv.org/pdf/2103.16022 |
| Representation range needs for 16-bit neural network training |
https://arxiv.org/pdf/2103.15940 |
| Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data |
https://arxiv.org/pdf/2103.15914 |
| Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks |
https://arxiv.org/pdf/2103.15578 |
| Self-Supervised Visibility Learning for Novel View Synthesis |
https://arxiv.org/pdf/2103.15407 |
| Explaining Representation by Mutual Information |
https://arxiv.org/pdf/2103.15114 |
| Self-supervised Discriminative Feature Learning for Multi-view Clustering |
https://arxiv.org/pdf/2103.15069 |
| Self-supervised Graph Neural Networks without explicit negative sampling |
https://arxiv.org/pdf/2103.14958 |
| Categorical Representation Learning: Morphism is All You Need |
https://arxiv.org/pdf/2103.14770 |
| Quantum Self-Supervised Learning |
https://arxiv.org/pdf/2103.14653 |
| Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification |
https://arxiv.org/pdf/2103.14267 |
| Self-Supervised Training Enhances Online Continual Learning |
https://arxiv.org/pdf/2103.14010 |
| Rethinking Deep Contrastive Learning with Embedding Memory |
https://arxiv.org/pdf/2103.14003 |
| Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning |
https://arxiv.org/pdf/2103.13885 |
| Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting |
https://arxiv.org/pdf/2103.13716 |
| Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels |
https://arxiv.org/pdf/2103.13646 |
| Rethinking Self-Supervised Learning: Small is Beautiful |
https://arxiv.org/pdf/2103.13559 |
| A Broad Study on the Transferability of Visual Representations with Contrastive Learning |
https://arxiv.org/pdf/2103.13517 |
| Jo-SRC: A Contrastive Approach for Combating Noisy Labels |
https://arxiv.org/pdf/2103.13029 |
| Supporting Clustering with Contrastive Learning |
https://arxiv.org/pdf/2103.12953 |
| Region Similarity Representation Learning |
https://arxiv.org/pdf/2103.12902 |
| Leveraging background augmentations to encourage semantic focus in self-supervised contrastive learning |
https://arxiv.org/pdf/2103.12719 |
| Self-Supervised Pretraining Improves Self-Supervised Pretraining |
https://arxiv.org/pdf/2103.12718 |
| Self-supervised representation learning from 12-lead ECG data |
https://arxiv.org/pdf/2103.12676 |
| Revisiting Self-Supervised Monocular Depth Estimation |
https://arxiv.org/pdf/2103.12496 |
| BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search |
https://arxiv.org/pdf/2103.12424 |
| Contrastive Reasoning in Neural Networks |
https://arxiv.org/pdf/2103.12329 |
| SSD: A Unified Framework for Self-Supervised Outlier Detection |
https://arxiv.org/pdf/2103.12051 |
| Self-supervised Representation Learning with Relative Predictive Coding |
https://arxiv.org/pdf/2103.11275 |
| Efficient Visual Pretraining with Contrastive Detection |
https://arxiv.org/pdf/2103.10957 |
| UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning |
https://arxiv.org/pdf/2103.10773 |
| Space-Time Crop & Attend: Improving Cross-modal Video Representation Learning |
https://arxiv.org/pdf/2103.10211 |
| Self-Supervised Adaptation for Video Super-Resolution |
https://arxiv.org/pdf/2103.10081 |
| Reconsidering Representation Alignment for Multi-view Clustering |
https://arxiv.org/pdf/2103.07738 |
| Spatially Consistent Representation Learning |
https://arxiv.org/pdf/2103.06122 |
| Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones |
https://arxiv.org/pdf/2103.05959 |
| VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples |
https://arxiv.org/pdf/2103.05905 |
| Self-Supervision by Prediction for Object Discovery in Videos |
https://arxiv.org/pdf/2103.05669 |
| Multimodal Representation Learning via Maximization of Local Mutual Information |
https://arxiv.org/pdf/2103.04537 |
| Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations |
https://arxiv.org/pdf/2103.04167 |
| Liver Fibrosis and NAS scoring from CT images using self-supervised learning and texture encoding |
https://arxiv.org/pdf/2103.03761 |
| Self-Supervised Longitudinal Neighbourhood Embedding |
https://arxiv.org/pdf/2103.03840 |
| Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification |
https://arxiv.org/pdf/2103.03629 |
| Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis |
https://arxiv.org/pdf/2103.03568 |
| Barlow Twins: Self-Supervised Learning via Redundancy Reduction |
https://arxiv.org/pdf/2103.03230 |
| Contrastive Learning Meets Transfer Learning: A Case Study In Medical Image Analysis |
https://arxiv.org/pdf/2103.03166 |
| Self-supervised deep convolutional neural network for chest X-ray classification |
https://arxiv.org/pdf/2103.03055 |
| Deep Clustering by Semantic Contrastive Learning |
https://arxiv.org/pdf/2103.02662 |
| Self-supervised Pretraining of Visual Features in the Wild |
https://arxiv.org/pdf/2103.01988 |
| There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge |
https://arxiv.org/pdf/2103.01353 |
| A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning |
https://arxiv.org/pdf/2103.00845 |
| Self-supervised Low Light Image Enhancement and Denoising |
https://arxiv.org/pdf/2103.00832 |
| Graph Self-Supervised Learning: A Survey |
https://arxiv.org/pdf/2103.00111 |
| Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation |
https://arxiv.org/pdf/2102.11614 |
| Representation Disentanglement for Multi-modal brain MR Analysis |
https://arxiv.org/pdf/2102.11456 |
| Towards Causal Representation Learning |
https://arxiv.org/pdf/2102.11107 |
| Self-Supervised Learning of Graph Neural Networks: A Unified Review |
https://arxiv.org/pdf/2102.10757 |
| Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning |
https://arxiv.org/pdf/2102.10680 |
| Contrastive Self-supervised Neural Architecture Search |
https://arxiv.org/pdf/2102.10557 |
| Do Generative Models Know Disentanglement? Contrastive Learning is All You Need |
https://arxiv.org/pdf/2102.10543 |
| Self-Supervised Learning via multi-Transformation Classification for Action Recognition |
https://arxiv.org/pdf/2102.10378 |
| Contrastive Learning Inverts the Data Generating Process |
https://arxiv.org/pdf/2102.08850 |
| Instance Localization for Self-supervised Detection Pretraining |
https://arxiv.org/pdf/2102.08318 |
| Learning Invariant Representations using Inverse Contrastive Loss |
https://arxiv.org/pdf/2102.08343 |
| Self-Supervised Features Improve Open-World Learning |
https://arxiv.org/pdf/2102.07848 |
| Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning |
https://arxiv.org/pdf/2102.06866 |
| Understanding self-supervised Learning Dynamics without Contrastive Pairs |
https://arxiv.org/pdf/2102.06810 |
| Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning |
https://arxiv.org/pdf/2102.06605 |
| Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning |
https://arxiv.org/pdf/2102.04848 |
| A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning |
https://arxiv.org/pdf/2102.03837 |
| Self-supervised driven consistency training for annotation efficient histopathology image analysis |
https://arxiv.org/pdf/2102.03897 |
| Echo-SyncNet: Self-supervised Cardiac View Synchronization in Echocardiography |
https://arxiv.org/pdf/2102.02287 |
| Fast Concept Mapping: The Emergence of Human Abilities in Artificial Neural Networks when Learning Embodied and Self-Supervised |
https://arxiv.org/pdf/2102.02153 |
| Self-Supervised Representation Learning for RGB-D Salient Object Detection |
https://arxiv.org/pdf/2101.12482 |
| Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning |
https://arxiv.org/pdf/2101.08732 |
| Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning |
https://arxiv.org/pdf/2101.08482 |
| TCLR: Temporal Contrastive Learning for Video Representation |
https://arxiv.org/pdf/2101.07974 |
| JigsawGAN: Self-supervised Learning for Solving Jigsaw Puzzles with Generative Adversarial Networks |
https://arxiv.org/pdf/2101.07555 |
| Momentum^2 Teacher: Momentum Teacher with Momentum Statistics for Self-Supervised Learning |
https://arxiv.org/pdf/2101.07525 |
| Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup |
https://arxiv.org/pdf/2101.06983 |
| Self-Supervised Representation Learning from Flow Equivariance |
https://arxiv.org/pdf/2101.06553 |
| SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning |
https://arxiv.org/pdf/2101.06480 |
| Task-driven Self-supervised Bi-channel Networks Learning for Diagnosis of Breast Cancers with Mammography |
https://arxiv.org/pdf/2101.06228 |
| Self-Supervised Learning for Segmentation |
https://arxiv.org/pdf/2101.05456 |
| Big Self-Supervised Models Advance Medical Image Classification |
https://arxiv.org/pdf/2101.05224 |
| COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction |
https://arxiv.org/pdf/2101.04909 |
| SEED: Self-supervised Distillation For Visual Representation |
https://arxiv.org/pdf/2101.04731 |
| Explicit homography estimation improves contrastive self-supervised learning |
https://arxiv.org/pdf/2101.04713 |
| Estimating Galactic Distances From Images Using Self-supervised Representation Learning |
https://arxiv.org/pdf/2101.04293 |
| Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning |
https://arxiv.org/pdf/2101.04269 |
| Contextual Classification Using Self-Supervised Auxiliary Models for Deep Neural Networks |
https://arxiv.org/pdf/2101.03057 |
| Contrastive Learning for Recommender System |
https://arxiv.org/pdf/2101.01317 |
| With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations |
https://arxiv.org/abs/2104.14548 |