Node Classification On Cora 3
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Accuracy |
|---|---|
| inductive-representation-learning-on-large | 64.2% |
| view-consistent-heterogeneous-network-on | 83.1% |
| break-the-ceiling-stronger-multi-scale-deep | 81.92% |
| extract-the-knowledge-of-graph-neural | 84.18% |
| convolutional-networks-on-graphs-for-learning | 71.7% |
| mutual-teaching-for-graph-convolutional | 78.5% |
| graph-attention-networks | 56.8% |
| lanczosnet-multi-scale-deep-graph | 77.7 ± 2.4 |
| lanczosnet-multi-scale-deep-graph | 76.3 ± 2.3 |
| gated-graph-sequence-neural-networks | 73.1% |
| convolutional-neural-networks-on-graphs-with | 62.1% |
| break-the-ceiling-stronger-multi-scale-deep | 79.52% |
| break-the-ceiling-stronger-multi-scale-deep | 80.96% |
| break-the-ceiling-stronger-multi-scale-deep | 80.72% |
| diffusion-convolutional-neural-networks | 76.7% |