Node Classification On Amazon Computers 1
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | Accuracy |
|---|---|
| inferring-from-references-with-differences | 90.74% |
| classic-gnns-are-strong-baselines-reassessing | 93.25±0.14 |
| mitigating-degree-biases-in-message-passing | 91.45±0.58 |
| classic-gnns-are-strong-baselines-reassessing | 93.99±0.12 |
| mixture-of-experts-meets-decoupled-message | 92.17±0.50 |
| distilling-self-knowledge-from-contrastive | 88.85% |
| classic-gnns-are-strong-baselines-reassessing | 94.09±0.37 |
| mixture-of-experts-meets-decoupled-message | 91.85±0.39 |
| distilling-self-knowledge-from-contrastive | 89.42% |
| mixture-of-experts-meets-decoupled-message | 91.98±0.46 |
| distilling-self-knowledge-from-contrastive | 89.49% |
| distilling-self-knowledge-from-contrastive | 89.44% |