ER
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Maximum Independent Set | ER [700-800] | Solution Size44.87 | 58 | |
| Emotion Recognition | ER | Accuracy66.1 | 33 | |
| Causal Discovery | ER5 n = 50, h = 5 synthetic | FDR4 | 15 | |
| Maximum Independent Set | ER [9000-11000] | MIS Size384.38 | 13 | |
| Maximum Independent Set | ER [700-800] DIMES (test) | Approximation Ratio (ApR)1.006 | 11 | |
| Node-level Regression Uncertainty Quantification | ER | PICP100 | 9 | |
| Curvilinear Structure Segmentation | ER (test) | Dice Coefficient84.52 | 9 | |
| Node-level classification | ER 15K | MCC0.915 | 9 | |
| Uncertainty Quantification | ER Synthetic | MPE0.15 | 8 | |
| Robustness Prediction | ER (Dynamic) | Mean Error0.0005 | 8 | |
| Robustness Prediction | ER Static | Mean Error0.0028 | 8 | |
| Relational Inference | ER-50 CMN | AUC99.75 | 7 | |
| Node-level classification | ER 30K | Accuracy76 | 7 | |
| Node-level classification | ER 30K | MCC0.872 | 7 | |
| Epidemic parameter estimation | ER | RMSE (beta)0 | 5 | |
| Minimum Vertex Cover | ER (400,500) slice (test) | Avg Vertex Cover Size415.52 | 5 | |
| Minimum Vertex Cover | ER (100,200) (test) | Avg Vertex Cover Size122.76 | 5 | |
| Minimum Vertex Cover | ER (50,100) slice (test) | Avg Vertex Cover Size54.67 | 5 | |
| MaxCut | ER800w | Cut Size1,881.8 | 4 | |
| MaxCut | ER200w | Cut Size399.25 | 4 | |
| Maximum Cut | ER (400,500) (test) | Avg Cut Size16,491.6 | 4 | |
| Graph alignment | ER sparse noise 0.1 | NCE899 | 3 | |
| Causal Discovery | ER (30, 60) | SHD17.52 | 3 | |
| Causal Discovery | ER (10, 20) | SHD1.44 | 3 |
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