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Articles by David Van Vranken
Mechanism-Aware Deep Learning for Polar Reaction Prediction
Performance on Manually Curated Data Set We train all models on 5 folds of the manually curated data set. The results comparing the performance of the trained models on the test splits can be seen in Table 1 . Table 1. Top-N Accuracy of Trained Models (Mean ± Std) Although the Siamese two-stage model allows for improved interpretability due to its direct prediction of arrows, Chemformer yielded the most accurate predictions among all nonensemble models.
Mechanism-Aware Deep Learning for Polar Reaction Prediction
Journal of the American Chemical Society Cite this: J. Am. Chem. Soc. 2025, XXXX, XXX Click to copy citationCitation copied! . This publication is licensed under CC-BY 4.0 . You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.
Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction
Journal of Chemical Information and Modeling Cite this: J. Chem. Inf. Model. 2025, XXXX, XXX Click to copy citationCitation copied! . This publication is licensed under CC-BY-NC-ND 4.0 . You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted.
Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction
Introduction Click to copy section linkSection link copied! Attaining chemist-level performance in predicting the outcomes of chemical reactions remains an unresolved challenge in computational chemistry. A solution to this challenge would have applications in many areas of chemistry both in the laboratory, for instance in synthesis, retrosynthesis, and drug design; and in nature, for instance: in biology and atmospheric chemistry.
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