SBM
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Graph Generation | SBM | VUN0.975 | 51 | |
| Graph Generation | SBM | Degree11.5 | 18 | |
| Fair Graph Clustering | SBM uni. xi in [0.4, 0.6], n = 5000 | Clustering Error (CE)0.52 | 12 | |
| Fair Graph Clustering | SBM uni. xi in [0, 0.2], n = 5000 | Clustering Error (CE)0.52 | 12 | |
| Fair Graph Clustering | SBM uni. xi in [0.4, 0.6], n = 1000 | Cross-Entropy0.51 | 12 | |
| Fair Graph Clustering | SBM uni. xi in [0, 0.2], n = 1000 | Clustering Error (CE)0.52 | 12 | |
| Synthetic Graph Generation | SBM20k | Degree154.16 | 9 | |
| Robustness Prediction | SBM Dynamic | Mean Error0.0005 | 8 | |
| Robustness Prediction | SBM Static | Mean Error0.0042 | 8 | |
| Node Clustering | SBM (k=3, n=3000, q=0.002) (test) | Error Rate0 | 8 | |
| Link Prediction | SBM synthetic (test) | Average MAP0.9648 | 8 | |
| Directed Graph Generation | SBM | Ratio1.5 | 7 | |
| Graph Classification | SBM 85/15 stratified Synthetic (train test) | Accuracy92.26 | 7 | |
| Link Prediction | SBM | mAP19.89 | 7 | |
| Node Classification | SBM hetero. | Accuracy (Clean)86.5 | 6 | |
| Graph Generation | SBM | Clustering Coefficient0.0588 | 4 | |
| Cerebral Lesion Segmentation | SBM | Dice67.53 | 3 | |
| Topological Preservation Analysis | SBM | Kappa FR3.998 | 3 |
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