Node Classification On Cluster
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Accuracy |
|---|---|
| benchmarking-graph-neural-networks | 76.08 |
| exphormer-sparse-transformers-for-graphs | 78.22±0.045 |
| graph-inductive-biases-in-transformers | 80.026 |
| automatic-relation-aware-graph-network | 77.35 |
| graph-transformers-without-positional | 77.456 |
| unlocking-the-potential-of-classic-gnns-for | 79.128 ± 0.235 |
| recipe-for-a-general-powerful-scalable-graph | 77.95 |
| graph-propagation-transformer-for-graph | 78.07 |
| edge-augmented-graph-transformers-global-self | 79.232 |
| topology-informed-graph-transformer | 78.033 |
| ckgconv-general-graph-convolution-with | 79.003 |
| learning-long-range-dependencies-on-graphs | 78.189 ± 0.188 |