Graph Classification On Hiv
Metrics
ROC-AUC
Results
Performance results of various models on this benchmark
Model Name | ROC-AUC | Paper Title | Repository |
|---|---|---|---|
| G-Tuning | 77.33 | Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns | - |
| GMT | 77.56 | Accurate Learning of Graph Representations with Graph Multiset Pooling | - |
| GTOT-Tuning | 78.2 | Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport | - |
0 of 3 row(s) selected.