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Link Prediction On Decagon
Metrics
AUPRC
AUROC
mAP@50
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||||
|---|---|---|---|---|---|
| TIP | 0.890 | 0.914 | 0.890 | Tri-graph Information Propagation for Polypharmacy Side Effect Prediction | |
| Decagon | 0.832 | 0.872 | 0.803 | Modeling polypharmacy side effects with graph convolutional networks |
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