Node Classification On Nell
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| GraphVAT | 64.7% | Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure | - |
| GCN | 66.0 | Semi-Supervised Classification with Graph Convolutional Networks | - |
| DFNet-ATT | 68.8 ± 0.3 | DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters | - |
| Planetoid* | 61.9% | Revisiting Semi-Supervised Learning with Graph Embeddings | - |
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