Node Classification On Amz Photo
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| GLNN | 92.11± 1.08% | - | - |
| GraphSAGE | 95.03% | - | - |
| HH-GraphSAGE | 94.55% | - | - |
| NCSAGE | 95.93 ± 0.36 | - | - |
| HH-GCN | 94.52% | - | - |
| CGT | 95.73±0.84 | - | - |
| Graph InfoClust (GIC) | 90.4 ± 1.0 | - | - |
| JK (Heat Diffusion) | 92.93% | - | - |
| Exphormer | 95.35±0.22% | - | - |
| SIGN | 91.72 ± 1.20 | - | - |
| NCGCN | 95.45 ± 0.45 | - | - |
| DAGNN (Ours) | 92% | - | - |
| GCN | 93.59% | - | - |
| CPF-ind-GAT | 94.10% | - | - |
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