GAUCHE: A Library for Gaussian Processes in Chemistry

Abstract

We introduce GAUCHE, an open-source library for GAUssian processes in CHEmistry. Gaussian processes have long been a cornerstone of probabilistic machine learning, affording particular advantages for uncertainty quantification and Bayesian optimisation. Extending Gaussian processes to molecular representations, however, necessitates kernels defined over structured inputs such as graphs, strings and bit vectors. By providing such kernels in a modular, robust and easy-to-use framework, we seek to enable expert chemists and materials scientists to make use of state-of-the-art black-box optimization techniques. Motivated by scenarios frequently encountered in practice, we showcase applications for GAUCHE in molecular discovery, chemical reaction optimisation and protein design. The codebase is made available at https://github.com/leojklarner/gauche.

Cite

Text

Griffiths et al. "GAUCHE: A Library for Gaussian Processes in Chemistry." Neural Information Processing Systems, 2023.

Markdown

[Griffiths et al. "GAUCHE: A Library for Gaussian Processes in Chemistry." Neural Information Processing Systems, 2023.](https://mlanthology.org/neurips/2023/griffiths2023neurips-gauche/)

BibTeX

@inproceedings{griffiths2023neurips-gauche,
  title     = {{GAUCHE: A Library for Gaussian Processes in Chemistry}},
  author    = {Griffiths, Ryan-Rhys and Klarner, Leo and Moss, Henry and Ravuri, Aditya and Truong, Sang and Du, Yuanqi and Stanton, Samuel and Tom, Gary and Rankovic, Bojana and Jamasb, Arian and Deshwal, Aryan and Schwartz, Julius and Tripp, Austin and Kell, Gregory and Frieder, Simon and Bourached, Anthony and Chan, Alex and Moss, Jacob and Guo, Chengzhi and Dürholt, Johannes Peter and Chaurasia, Saudamini and Park, Ji Won and Strieth-Kalthoff, Felix and Lee, Alpha and Cheng, Bingqing and Aspuru-Guzik, Alan and Schwaller, Philippe and Tang, Jian},
  booktitle = {Neural Information Processing Systems},
  year      = {2023},
  url       = {https://mlanthology.org/neurips/2023/griffiths2023neurips-gauche/}
}