Node Classification On Wiki Vote
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| GCN_cheby (Kipf and Welling, 2017) | 49.5 | - | - |
| DEMO-Net(weight) | 99.8 | - | - |
| Union (Li et al., 2018) | 46.3 | - | - |
| GraphSAGE (Hamilton et al., [2017a]) | 24.5 | - | - |
| GCN (Kipf and Welling, 2017) | 32.9 | - | - |
| GAT (Velickovic et al., 2018) | 59.4 | - | - |
0 of 6 row(s) selected.