GAUCHE: A Library for Gaussian Processes in Chemistry

Ryan-Rhys Griffiths; Leo Klarner; Henry B. Moss; Aditya Ravuri; Sang Truong; Samuel Stanton; Gary Tom; Bojana Rankovic; Yuanqi Du; Arian Jamasb; Aryan Deshwal; Julius Schwartz; Austin Tripp; Gregory Kell; Simon Frieder; Anthony Bourached; Alex Chan; Jacob Moss; Chengzhi Guo; Johannes Durholt; Saudamini Chaurasia; Felix Strieth-Kalthoff; Alpha A. Lee; Bingqing Cheng; Alán Aspuru-Guzik; Philippe Schwaller; Jian Tang

arXiv · 2212.04450

GAUCHE: A Library for Gaussian Processes in Chemistry

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Abstract

We introduce GAUCHE, a 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 chemical representations, however, is nontrivial, necessitating kernels defined over structured inputs such as graphs, strings and bit vectors. By defining such kernels in GAUCHE, we seek to open the door to powerful tools for uncertainty quantification and Bayesian optimisation in chemistry. Motivated by scenarios frequently encountered in experimental chemistry, we showcase applications for GAUCHE in molecular discovery and chemical reaction optimisation. The codebase is made available at https://github.com/leojklarner/gauche

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physics.chem-ph cond-mat.mtrl-sci cs.LG

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Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Samuel Stanton, Gary Tom, Bojana Rankovic, Yuanqi Du, Arian Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Durholt, Saudamini Chaurasia, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang. 2022-12-06. GAUCHE: A Library for Gaussian Processes in Chemistry. https://arxiv.org/abs/2212.04450

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