SCROP Transformer model with neural syntax corrector reaches 59% accuracy on retrosynthesis benchmarks, outperforming prior deep learning methods by over 21 points and template-based methods by over 6 points, with 1.7 times higher accuracy on unseen compounds.
Journal of the Chemical Society, Transactions 1917, 111, 762-768
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Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
SCROP Transformer model with neural syntax corrector reaches 59% accuracy on retrosynthesis benchmarks, outperforming prior deep learning methods by over 21 points and template-based methods by over 6 points, with 1.7 times higher accuracy on unseen compounds.