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# Honegumi: An Interface for Accelerating the Adoption of Bayesian Optimization in the Experimental Sciences
# Honegumi: An Interface for Accelerating the Adoption of Bayesian Optimization in the Experimental Sciences [![arXiv](https://img.shields.io/badge/arXiv-2502.06815-red.svg)](https://arxiv.org/abs/2502.06815)

```{tip}
New to Bayesian optimization? Start with [A Gentle Introduction to Bayesian Optimization](https://youtu.be/IVaWl2tL06c) and explore our [concept guides](https://honegumi.readthedocs.io/en/latest/concepts.html) and [coding tutorials](https://honegumi.readthedocs.io/en/latest/tutorials.html) on key optimization principles.
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<iframe width="560" height="315" src="https://www.youtube.com/embed/T5DWycXu1SY?si=dLl83jYQSntXOPqx" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

## Citing

If you find Honegumi useful, please consider citing:

> Baird, Sterling G., Andrew R. Falkowski, and Taylor D. Sparks. "Honegumi: An Interface for Accelerating the Adoption of Bayesian Optimization in the Experimental Sciences." *arXiv*, February 4, 2025. https://doi.org/10.48550/arXiv.2502.06815.
```bibtex
@misc{baird_honegumi_2025,
title = {Honegumi: {{An Interface}} for {{Accelerating}} the {{Adoption}} of {{Bayesian Optimization}} in the {{Experimental Sciences}}},
shorttitle = {Honegumi},
author = {Baird, Sterling G. and Falkowski, Andrew R. and Sparks, Taylor D.},
year = {2025},
month = feb,
number = {arXiv:2502.06815},
eprint = {2502.06815},
primaryclass = {cs},
publisher = {arXiv},
doi = {10.48550/arXiv.2502.06815},
archiveprefix = {arXiv},
keywords = {Computer Science - Machine Learning,Condensed Matter - Materials Science},
}
```

Zenodo snapshots of the GitHub releases (beginning with `v0.3.2`) are available at [![DOI](https://zenodo.org/badge/658136354.svg)](https://doi.org/10.5281/zenodo.14949415)

## Contents

```{toctree}
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