Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias

Machine learning algorithms offer new possibilities for automating reaction procedures. The present paper investigates automated reaction’s prediction with Molecular Transformer, the state-of-the-art model for reaction prediction, proposing a new debiased dataset for a realistic assessment of the mo...

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Auteurs principaux: Dávid Péter Kovács, William McCorkindale, Alpha A. Lee
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/f5f5a1b384fd4609aa785325aa34d776
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