Node Anomaly Detection on Yelp
85.23PrecisionHGUN
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| HGUNModel Category=HyperGraph U-Net2026.06 | 85.23 | — | — | 82.72 | 77.32 | 80.26 | |
| MinCut + GCNModel Category=Graph U-Nets, Backbone=GCN, Pooling=MinCutPooling2026.06 | 83.72 | — | — | 76.23 | 72.81 | 69.41 | |
| BWGNNModel Category=AD GNNs2026.06 | 81.28 | — | — | 81.92 | 72.32 | 82.56 | |
| H²-FDetectorModel Category=AD GNNs2026.06 | 78.77 | — | — | 81.64 | 70.78 | 84.61 | |
| FAGCNModel Category=GNNs2026.06 | 71.08 | — | — | 70.86 | 61.11 | 70.64 | |
| TopK + GCNModel Category=Graph U-Nets, Backbone=GCN, Pooling=TopKPooling2026.06 | 70.33 | — | — | 73.35 | 71.33 | 67.79 | |
| CARE-GNNModel Category=AD GNNs2026.06 | 69.43 | — | — | 70.86 | 60.4 | 72.32 | |
| RioGNNModel Category=AD GNNs2026.06 | 68.82 | — | — | 73.52 | 61.61 | 78.54 | |
| HGXConvModel Category=HyperGNNs2026.06 | 68.63 | — | — | 72.37 | 72.27 | 76.32 | |
| HNHNModel Category=HyperGNNs2026.06 | 65.73 | — | — | 63.95 | 65.28 | 62.21 | |
| GPRGNNModel Category=GNNs2026.06 | 64.89 | — | — | 69.84 | 57.34 | 75.16 | |
| GATModel Category=GNNs2026.06 | 45.42 | — | — | 53.13 | 42.77 | 62.15 | |
| HGNNModel Category=HyperGNNs2026.06 | 41.73 | — | — | 56.5 | 34.21 | 76.5 | |
| HGATModel Category=HyperGNNs2026.06 | 40.93 | — | — | 47.51 | 46.98 | 55.15 | |
| GCNModel Category=GNNs2026.06 | 31.55 | — | — | 49.46 | 36.67 | 77.53 | |
| All-in-One-UTraining Strategy=Multi-task2024.11 | — | — | 50.01 | — | — | — | |
| AMNetTraining Strategy=Single-level2024.11 | — | — | 81.42 | — | — | — | |
| BernNetTraining Strategy=Single-level2024.11 | — | — | 81.48 | — | — | — | |
| BWGNNTraining Strategy=Single-level2024.11 | — | — | 83.11 | — | — | — | |
| GATTraining Strategy=Single-level2024.11 | — | — | 77.4 | — | — | — | |
| GCNBackbone=GCN, Method Category=Node-level2024.11 | — | 20.58 | — | — | — | — | |
| GCNTraining Strategy=Single-level2024.11 | — | — | 57.62 | — | — | — | |
| GINTraining Strategy=Single-level2024.11 | — | — | 74.46 | — | — | — | |
| GraphPrompt-UTraining Strategy=Multi-task2024.11 | — | — | 50.71 | — | — | — | |
| GraphSAGETraining Strategy=Single-level2024.11 | — | — | 82.12 | — | — | — | |
| PNATraining Strategy=Single-level2024.11 | — | — | 71.81 | — | — | — | |
| SGCTraining Strategy=Single-level2024.11 | — | — | 53.03 | — | — | — | |
| UniGADTraining Strategy=Multi-task, Backbone=GCN2024.11 | — | — | 63.22 | — | — | — | |
| UniGADTraining Strategy=Multi-task, Backbone=BWGNN2024.11 | — | — | 86.23 | — | — | — | |
| UniGAD-BWGBackbone=BWGNN, Method Category=UniGAD2024.11 | — | 27.42 | — | — | — | — | |
| UniGAD-GCNBackbone=GCN, Method Category=UniGAD2024.11 | — | 61 | — | — | — | — |