Heterogeneous Node Classification On Freebase
Métriques
Macro-F1
Micro-F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Macro-F1 | Micro-F1 | Paper Title | Repository |
|---|---|---|---|---|
| SeHGNN | 50.71 | 63.41 | Simple and Efficient Heterogeneous Graph Neural Network | |
| GAT | 40.74 | - | Graph Attention Networks | |
| Simple-HGN | - | 66.29 | Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks | |
| HGT | - | 60.51 | Heterogeneous Graph Transformer | |
| RpHGNN | - | 66.55 | Efficient Heterogeneous Graph Learning via Random Projection | |
| RGCN | - | 58.33 | Modeling Relational Data with Graph Convolutional Networks | |
| GCN | - | 60.23 | Semi-Supervised Classification with Graph Convolutional Networks | |
| SlotGAT | - | 66.83 | SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network | |
| NARS | - | 63.26 | Scalable Graph Neural Networks for Heterogeneous Graphs |
0 of 9 row(s) selected.