Driving school for self-driving labs

Kelsey L. Snapp · Keith A. Brown

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Scientific Computing and Data Management Machine Learning in Materials Science Human-Automation Interaction and Safety

Abstract

Self-driving labs benefit from occasional and asynchronous human interventions. We present a heuristic framework for how self-driving lab operators can interpret progress and make changes during a campaign.

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2018A Tutorial on Bayesian Optimization 2004Functional genomic hypothesis generation and experimentation by a robot scientist 2019Scalable Global Optimization via Local Bayesian Optimization 2018Efficient sampling algorithm for large-scale optimization under uncertainty problems

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