Node Classification on Chameleon (60%/20%/20% random)
76.08AccuracyACM-GCN+
Evaluation results
| Method | Links | ||
|---|---|---|---|
| ACM-GCN+2022.10 | 76.08 | 2.13 | |
| ACMII-GCN+2022.10 | 75.51 | 1.58 | |
| ChebNetIISplits=20 random 60%/20%/20% train/validation/test2022.10 | 71.37 | — | |
| GloGNN++2026.03 | 71.33 | — | |
| VR-GNN2026.03 | 71.21 | — | |
| P2GNNBackbone=ACM-GCN2026.03 | 69.87 | — | |
| GGCN2026.03 | 69.5 | — | |
| ClenshawGCN2022.10 | 69.44 | — | |
| ClenshawGCNSplits=20 random 60%/20%/20% train/validation/test2022.10 | 69.44 | — | |
| ACM-GCN2021.09 | 69.04 | — | |
| BernNetSplits=20 random 60%/20%/20% train/validation/test2022.10 | 68.53 | — | |
| ACM-Snowball-22021.09 | 68.51 | — | |
| ACM-GCN2026.03 | 68.45 | — | |
| ACM-Snowball-32021.09 | 68.4 | — | |
| ACMII-GCN2021.09 | 68.38 | — | |
| BernNet2026.03 | 68.29 | — | |
| GAT+JK2021.09 | 68.14 | — | |
| GAT+JK2026.03 | 68.14 | — | |
| ACMII-Snowball-22021.09 | 67.83 | — | |
| ACMII-Snowball-32021.09 | 67.53 | — | |
| GPRGNNSplits=20 random 60%/20%/20% train/validation/test2022.10 | 67.49 | — | |
| GPRGNN2022.10 | 67.48 | 0.4 | |
| GPRGNN*2021.09 | 67.48 | — | |
| GPRGNN2026.03 | 67.48 | — | |
| Snowball-32021.09 | 65.49 | — | |
| Snowball-32026.03 | 65.49 | — | |
| Snowball-22021.09 | 64.99 | — | |
| Snowball-22026.03 | 64.99 | — | |
| SGC-12021.09 | 64.86 | — | |
| GCN+JK2022.10 | 64.68 | — | |
| GCN+JK2021.09 | 64.68 | — | |
| GCN+JK2026.03 | 64.68 | — | |
| GCN2021.09 | 64.18 | — | |
| GAT*2021.09 | 63.9 | — | |
| GAT2026.03 | 63.9 | — | |
| ACM-SGC-12021.09 | 63.68 | — | |
| GCNII2022.10 | 63.44 | — | |
| GCNII*2021.09 | 62.8 | — | |
| SGC-22021.09 | 62.67 | — | |
| SGC-22026.03 | 62.67 | — | |
| GraphSAGE2021.09 | 62.15 | — | |
| ACM-GCNII*2021.09 | 61.66 | — | |
| Geom-GCN†2021.09 | 60.9 | — | |
| GCN2022.10 | 60.81 | — | |
| ACM-SGC-22021.09 | 60.48 | — | |
| GCNII2021.09 | 60.35 | — | |
| GCNII2026.03 | 60.35 | — | |
| ARMASplits=20 random 60%/20%/20% train/validation/test2022.10 | 60.21 | — | |
| ChebNetSplits=20 random 60%/20%/20% train/validation/test2022.10 | 59.51 | — | |
| H2GCN2021.09 | 59.39 | — | |
| ACM-GCNII2021.09 | 58.73 | — | |
| H2GCN2022.10 | 52.3 | — | |
| H2GCN2026.03 | 52.3 | — | |
| APPNPSplits=20 random 60%/20%/20% train/validation/test2022.10 | 52.15 | — | |
| APPNP*2021.09 | 51.91 | — | |
| FAGCN2021.09 | 49.47 | — | |
| FAGCN2026.03 | 49.47 | — | |
| att-Node-level NLSFssource=this paper2024.06 | 46.75 | — | |
| MLP-2*2021.09 | 46.72 | — | |
| MLP2026.03 | 46.72 | — | |
| MLP2022.10 | 46.59 | — | |
| ChebNetIIsource=[41]2024.06 | 43.42 | — | |
| GCNsource=[41]2024.06 | 38.15 | — | |
| ARMAsource=[41]2024.06 | 37.42 | — | |
| ChebNetsource=[41]2024.06 | 37.15 | — | |
| MixHop2022.10 | 36.28 | — | |
| MixHop2021.09 | 36.28 | — | |
| CayleyNetsource=this paper2024.06 | 34.52 | — | |
| GATsource=this paper2024.06 | 34.16 | — | |
| GPRGNNsource=[41]2024.06 | 33.03 | — | |
| APPNPsource=[41]2024.06 | 32.73 | — | |
| SAGEsource=this paper2024.06 | 31.77 | — |