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Drug Discovery On Muv
Metrics
AUC
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| TrimNet | 0.851 | TrimNet: learning molecular representation from triplet messages for biomedicine | - |
| GraphConv + dummy super node | 0.845 | Learning Graph-Level Representation for Drug Discovery | |
| GraphConv | 0.836 | Convolutional Networks on Graphs for Learning Molecular Fingerprints | |
| ContextPred | 0.813 | Strategies for Pre-training Graph Neural Networks | |
| RNN-DFS | 0.648 | Relational Pooling for Graph Representations |
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