Graph Clustering On Pubmed
Métriques
ACC
NMI
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | ACC | NMI | Paper Title | Repository |
|---|---|---|---|---|
| RWR-GAE | 72.6 | 35.5 | RWR-GAE: Random Walk Regularization for Graph Auto Encoders | |
| VGAE | 65.48 | - | Variational Graph Auto-Encoders | |
| DAEGC+GSCAN† | - | 31.7 | GSCAN: Graph Stability Clustering for Applications With Noise Using Edge-Aware Excess-of-Mass | |
| RWR-VGAE | 73.6 | 34.6 | RWR-GAE: Random Walk Regularization for Graph Auto Encoders | |
| R-GMM-VGAE | 74.0 | 33.4 | Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering | |
| R-DGAE | 71.4 | 34.4 | Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering | |
| AGC | 69.78 | 31.59 | Attributed Graph Clustering via Adaptive Graph Convolution |
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