Dynamic Link Prediction on Enron Emails
AP
- 2018-09-07 — DynAERNN: AP 87.43
- 2019-02-26 — EGCN-H: AP 88.29
- 2019-08-26 — SI-VGRNN: AP 93.93
- 2022-04-24 — Euler: AP 94.1
| Rank | Model | AP | AUC | MRR | Paper | Code | Year |
|---|---|---|---|---|---|---|---|
| 1 | Euler | 94.10 | 93.15 | – | Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction | iHeartGraph/Euler | 2022 |
| 2 | SI-VGRNN | 93.93 | 94.44 | – | Variational Graph Recurrent Neural Networks | VGraphRNN/VGRNN · marlin-codes/HTGN | 2019 |
| 3 | teneNCE | 93.65 | 93.54 | 0.315 | Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks | amrhssn/teneNCE | 2024 |
| 4 | VGRNN | 93.10 | 93.29 | – | Variational Graph Recurrent Neural Networks | VGraphRNN/VGRNN · marlin-codes/HTGN | 2019 |
| 5 | EGCN-H | 88.29 | 89.33 | – | EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs | dmlc/dgl · benedekrozemberczki/pytorch_geometric_temporal · IBM/EvolveGCN · +7 | 2019 |
| 6 | DynAERNN | 87.43 | 89.37 | – | dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning | palash1992/DynamicGEM | 2018 |
| 7 | EGCN-O | 84.28 | 86.55 | – | EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs | dmlc/dgl · benedekrozemberczki/pytorch_geometric_temporal · IBM/EvolveGCN · +7 | 2019 |