Dynamic Link Prediction On Dblp Temporal
Métriques
AP
AUC
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AP | AUC | Paper Title | Repository |
|---|---|---|---|---|
| Euler | 89.03 | 86.54 | Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction | |
| EGCN-H | 83.87 | 80.80 | EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs | |
| EGCN-O | 81.43 | 78.63 | EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs | |
| VGRNN | 87.77 | 85.95 | Variational Graph Recurrent Neural Networks | |
| SI-VGRNN | 88.36 | 85.45 | Variational Graph Recurrent Neural Networks | |
| teneNCE | 90.45 | 88.25 | Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks | |
| DynAERNN | 81.84 | 76.06 | dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning |
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