“Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models† †Electronic supplementary information (ESI) available: Time-split test set and example predictions, together with attention weights, confidence and token probabilities. See DO

@article{Schwaller2018FoundIT,
  title={“Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models† †Electronic supplementary information (ESI) available: Time-split test set and example predictions, together with attention weights, confidence and token probabilities. See DO},
  author={P. Schwaller and T. Gaudin and D. Lanyi and C. Bekas and T. Laino},
  journal={Chemical Science},
  year={2018},
  volume={9},
  pages={6091 - 6098}
}
Using a text-based representation of molecules, chemical reactions are predicted with a neural machine translation model borrowed from language processing. 
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