Roman-empire
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Node Classification | Roman-Empire | Accuracy94.77 | 327 | |
| Federated Learning | Roman-empire | Time Consumption (s)2.17 | 84 | |
| Node Classification | Roman-empire (test) | Accuracy92.92 | 66 | |
| Node Classification | Roman-empire heterophilic (test) | Accuracy94.77 | 49 | |
| Node Classification | Roman-empire non-overlapping subgraph partitioning | Accuracy71.95 | 45 | |
| Node Classification | Roman-empire overlapping subgraph partitioning | Accuracy65.66 | 39 | |
| Out-of-Distribution Detection | Roman Empire | Rank1 | 24 | |
| Node Classification | Roman-Empire original | Accuracy84.42 | 20 | |
| Node Classification | Roman-empire v1 (test) | Accuracy92.08 | 20 | |
| Node Classification | Roman-empire overlapping subgraph partitioning (10 Clients) | Accuracy67.22 | 15 | |
| Node Classification | Roman-empire non-overlapping subgraph partitioning (5 Clients) | Accuracy0.6867 | 13 | |
| O.O.D. detection | Roman Empire Far-Features | AUC-PR (Aleatoric)52.6 | 12 | |
| O.O.D. detection | Roman Empire Near-Features | AUC-PR (Aleatoric)41.9 | 12 | |
| O.O.D. detection | Roman Empire (LoC) | AUC-PR (Aleatoric)41.4 | 12 | |
| Out-of-Distribution Detection | Roman Empire Local Class (LoC) | AUC-ROC (Aleatoric)76.4 | 12 | |
| Vertex Classification | Roman-Empire | Mean Accuracy92.27 | 11 | |
| Node Classification | Roman Empire 95% (test) | Accuracy56.26 | 8 | |
| Graph Clustering | Roman-empire | Accuracy (ACC)34.57 | 8 | |
| Heterophilous Node Classification | Roman-Empire (test) | AP88.56 | 7 | |
| OOD Detection | Roman Empire | AUROC69.58 | 5 | |
| Out-of-Distribution Detection | Roman Empire (Near-Features) | AUC-ROC (Aleatoric)0.865 | 3 | |
| Out-of-Distribution Detection | Roman Empire Far-Features | AUC-ROC (Aleatoric)83 | 2 |
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