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Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...
Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...
Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...