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04/04/2022
On scientific understanding with artificial intelligence
Imagine an oracle that correctly predicts the outcome of every particle ...
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03/29/2022
Bayesian optimization with known experimental and design constraints for chemistry applications
Optimization strategies driven by machine learning, such as Bayesian opt...
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03/05/2021
Golem: An algorithm for robust experiment and process optimization
Numerous challenges in science and engineering can be framed as optimiza...
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03/05/2021
Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation
Bayesian optimization has emerged as a powerful strategy to accelerate s...
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10/08/2020
Olympus: a benchmarking framework for noisy optimization and experiment planning
Research challenges encountered across science, engineering, and economi...
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03/26/2020
Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry
Designing functional molecules and advanced materials requires complex i...
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05/31/2019
SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry
Graphs are ideal representations of complex, relational information. The...
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01/04/2018
PHOENICS: A universal deep Bayesian optimizer
In this work we introduce PHOENICS, a probabilistic global optimization ...
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07/20/2017