Node Classification on CS (test)
95.03AccuracySPGCL
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| SPGCLTraining Data=X, A2026.06 | 95.03 | — | — | — | — | |
| SGRLTraining Data=X, A2026.06 | 94.08 | — | — | — | — | |
| StrGCLTraining Data=X, A2026.06 | 94.06 | — | — | — | — | |
| CSGCLTraining Data=X, A2026.06 | 93.63 | — | — | — | — | |
| GCATraining Data=X, A2026.06 | 93.48 | — | — | — | — | |
| BGRLTraining Data=X, A2026.06 | 93.41 | — | — | — | — | |
| ProGCLTraining Data=X, A2026.06 | 93.36 | — | — | — | — | |
| AFGRL*Training Data=X, A2026.06 | 93.27 | — | — | — | — | |
| DGITraining Data=X, A2026.06 | 93.17 | — | — | — | — | |
| SIGNATraining Data=X, A2026.06 | 93.12 | — | — | — | — | |
| SCETraining Data=X, A2026.06 | 93.06 | — | — | — | — | |
| GRACETraining Data=X, A2026.06 | 93.05 | — | — | — | — | |
| GCNTraining Data=X, A, Y2026.06 | 93.03 | — | — | — | — | |
| E2NegTraining Data=X, A2026.06 | 92.99 | — | — | — | — | |
| LocalGCLTraining Data=X, A2026.06 | 92.52 | — | — | — | — | |
| APSBackbone=GCN, Significance level (alpha)=0.12024.05 | — | 0.9 | 1.48 | 71.31 | — | |
| Auto-GNNMaximum refinement budget=1002025.07 | — | — | — | — | 95.15 | |
| AutoTransferMaximum refinement budget=1002025.07 | — | — | — | — | 95.16 | |
| DAPSBackbone=GCN, Significance level (alpha)=0.12024.05 | — | 0.9 | 1.09 | 83.69 | — | |
| DesiGNNMaximum refinement budget=1002025.07 | — | — | — | — | 95.03 | |
| EAMaximum refinement budget=1002025.07 | — | — | — | — | 94.94 | |
| GraphGymMaximum refinement budget=1002025.07 | — | — | — | — | 94.71 | |
| GraphNASMaximum refinement budget=1002025.07 | — | — | — | — | 94.9 | |
| KBGMaximum refinement budget=1002025.07 | — | — | — | — | 94.71 | |
| M-DESIGNMaximum refinement budget=1002025.07 | — | — | — | — | 95.33 | |
| NAS-Bench-GraphMaximum refinement budget=1002025.07 | — | — | — | — | 93.88 | |
| RandomMaximum refinement budget=1002025.07 | — | — | — | — | 94.96 | |
| RAPSBackbone=GCN, Significance level (alpha)=0.12024.05 | — | 0.9 | 1 | 89.72 | — | |
| RLMaximum refinement budget=1002025.07 | — | — | — | — | 95.02 | |
| SNAPSBackbone=GCN, Significance level (alpha)=0.12024.05 | — | 0.899 | 1.02 | 88.29 | — | |
| Space OptimumMaximum refinement budget=1002025.07 | — | — | — | — | 95.33 |