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Extraction of organic chemistry grammar from unsupervised learning of chemical reactions

277 Citations2021
Philippe Schwaller, Benjamin Hoover, Jean‐Louis Reymond

This work demonstrates that Transformer Neural Networks learn atom-mapping information between products and reactants without supervision or human labeling, and provides the missing link between data-driven and rule-based approaches for numerous chemical reaction tasks.

Abstract

<jats:p>RXNmapper constructs coherent atom-mapping rules from raw chemical reactions using unsupervised training of neural networks.</jats:p>

Extraction of organic chemistry grammar from unsupervised le