Node Classification 벤치마크
Node Classification on London
Average Top-1 Accuracy
- 2025-03-12 — ChebNet: Average Top-1 Accuracy 49.4
- 2025-05-29 — IM-GCN: Average Top-1 Accuracy 58.9
| Rank | Model | Average Top-1 Accuracy | Paper | Code | Year |
|---|---|---|---|---|---|
| 1 | IM-GCN | 58.9 ± 0.1 | Improving the Effective Receptive Field of Message-Passing Neural Networks | bgu-cs-vil/im-mpnn | 2025 |
| 2 | ChebNet | 49.4 ± 0.4 | Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement | leonresearch/city-networks | 2025 |
| 3 | GraphSAGE | 48.2 ± 0.8 | Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement | leonresearch/city-networks | 2025 |
| 4 | SGFormer | 45.7 ± 0.3 | Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement | leonresearch/city-networks | 2025 |
| 5 | GCN | 43.8 ± 0.3 | Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement | leonresearch/city-networks | 2025 |