Nature Communications (Mar 2021)

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

  • Dávid Péter Kovács,
  • William McCorkindale,
  • Alpha A. Lee

DOI
https://doi.org/10.1038/s41467-021-21895-w
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 9

Abstract

Read online

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.