A hypergraph neural network with reaction-center-aware negative sampling achieves higher F1 scores than GCN/GAT/HGNN baselines for reaction virtual screening on USPTO subsets.
Simulated Annealing, pages 59--79
1 Pith paper cite this work, alongside 22 external citations. Polarity classification is still indexing.
1
Pith paper citing it
22
external citations · OpenAlex
citation-role summary
other 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
other 1polarities
unclear 1representative citing papers
citing papers explorer
-
ChemHGNN: A Hierarchical Hypergraph Neural Network for Reaction Virtual Screening and Discovery
A hypergraph neural network with reaction-center-aware negative sampling achieves higher F1 scores than GCN/GAT/HGNN baselines for reaction virtual screening on USPTO subsets.