Adding virtual nodes to a graph transformer and using gated attention fusion improves drug-target affinity prediction on Davis, Metz, and KIBA by small margins.
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ViDTA: Enhanced Drug-Target Affinity Prediction via Virtual Graph Nodes and Attention-based Feature Fusion
Adding virtual nodes to a graph transformer and using gated attention fusion improves drug-target affinity prediction on Davis, Metz, and KIBA by small margins.