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cs.LG2025
ChemHGNN: A Hierarchical Hypergraph Neural Network for Reaction Virtual Screening and Discovery
Xiaobao Huang, Yihong Ma, Anjali Gurajapu +4
Reaction virtual screening and discovery are fundamental challenges in chemistry and materials science, where traditional graph neural networks (GNNs) struggle to model multi-react…
cs.LG2020★ 12 cited
Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions
Serim Ryou, Michael R. Maser, Alexander Y. Cui +3
We present a systematic investigation using graph neural networks (GNNs) to model organic chemical reactions. To do so, we prepared a dataset collection of four ubiquitous reaction…