Heterogeneous Node Classification On Dblp 2
Metrics
Macro-F1
Micro-F1
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Macro-F1 | Micro-F1 |
|---|---|---|
| scalable-graph-neural-networks-for-1 | 94.18 | 94.61 |
| an-attention-based-graph-neural-network-for | 78.55 | 80.56 |
| are-we-really-making-much-progress-revisiting | 94.01 | 94.46 |
| graph-transformer-networks-1 | 93.52 | 93.97 |
| heterogeneous-graph-transformer | 93.01 | 93.49 |
| modeling-relational-data-with-graph | 91.52 | 92.07 |
| graph-attention-networks | - | 93.39 |
| slotgat-slot-based-message-passing-for | 94.95 | 95.31 |
| efficient-heterogeneous-graph-learning-via | 95.23 | 95.55 |
| simple-and-efficient-heterogeneous-graph | - | 95.24 |
| semi-supervised-classification-with-graph | 90.84 | 91.47 |