Node Classification On Texas
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| 2-HiGCN | 92.45±0.73 | - | - |
| HLP Concat | 87.57 ± 5.44 | - | - |
| MGNN + Hetero-S (8 layers) | 93.09 | - | - |
| Diag-NSD | 85.67 ± 6.95 | - | - |
| GGCN | 84.86 ± 4.55 | - | - |
| MixHop | 77.84 ± 7.73 | - | - |
| ACM-GCN+ | 88.38 ± 3.64 | - | - |
| UniG-Encoder | 85.40±5.3 | - | - |
| ACM-SGC-2 | 81.89 ± 4.53 | - | - |
| SADE-GCN | 86.49±5.12 | - | - |
| Geom-GCN-S | 59.73 | - | - |
| GloGNN++ | 84.05±4.90 | - | - |
| Gen-NSD | 82.97 ± 5.13 | - | - |
| LINKX+CausalMP | 57.36±0.60 | - | - |
| IIE-GNN | 85.84±4.23 | - | - |
| M2M-GNN | 89.19 ± 4.5 | - | - |
| DeltaGNN constant | 74.05±3.08 | - | - |
| LINKX | 74.60 ± 8.37 | - | - |
| NLMLP | 85.4 ± 3.8 | - | - |
| FSGNN | 87.30 ± 5.55 | - | - |
0 of 62 row(s) selected.