Heterogeneous Node Classification On Freebase
Metrics
Macro-F1
Micro-F1
Results
Performance results of various models on this benchmark
Model Name | 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 | - |
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