Nature Communications (Mar 2021)
Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
Abstract
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 model’s performance.