Drug Discovery On Hiv Dataset
Metriken
AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| GraphConv + dummy super node + focal loss | 0.851 | Learning Graph-Level Representation for Drug Discovery |
| GraphConv | 0.822 | Convolutional Networks on Graphs for Learning Molecular Fingerprints |
| TrimNet | 0.804 | TrimNet: learning molecular representation from triplet messages for biomedicine |
| ContextPred | 0.799 | Strategies for Pre-training Graph Neural Networks |
| RNN-DFS | 0.627 | Relational Pooling for Graph Representations |
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