Graph Classification On Hiv Dti 77
Metriken
Accuracy
F1
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy | F1 | Paper Title | Repository |
|---|---|---|---|---|
| SDBN | 65.9% | 65.6% | Structural Deep Network Embedding | - |
| IsoNN | 67.5% | 68.3% | IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification | - |
| GIN | 55.1% | 53.6% | How Powerful are Graph Neural Networks? | - |
| WL | 47.1% | 48.4% | - | - |
| IsoNN-fast | 60.1% | 61.9% | IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification | - |
| CNN | 54.3% | 55.7% | ImageNet Classification with Deep Convolutional Neural Networks | - |
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