Node Classification on Squirrel (60%/20%/20% random splits)
62.14AccuracyClenshawGCN
Evaluation Results
| Method | Links | |
|---|---|---|
| ClenshawGCN2022.10 | 62.14 | |
| ClenshawGCNSplits=20 random 60%/20%/20% train/validation/test2022.10 | 62.14 | |
| ACM-GCN2021.09 | 58.02 | |
| ChebNetIISplits=20 random 60%/20%/20% train/validation/test2022.10 | 57.72 | |
| ACM-Snowball-22021.09 | 55.97 | |
| ACM-Snowball-32021.09 | 55.73 | |
| ACMII-GCN2021.09 | 54.53 | |
| ACMII-Snowball-22021.09 | 53.48 | |
| GCN+JK2022.10 | 53.4 | |
| GCN+JK2021.09 | 53.4 | |
| ACMII-Snowball-32021.09 | 52.31 | |
| GAT+JK2021.09 | 52.28 | |
| BernNetSplits=20 random 60%/20%/20% train/validation/test2022.10 | 51.39 | |
| GPRGNNSplits=20 random 60%/20%/20% train/validation/test2022.10 | 50.43 | |
| GPRGNN*2021.09 | 49.93 | |
| Snowball-32021.09 | 48.25 | |
| Snowball-22021.09 | 47.88 | |
| SGC-12021.09 | 47.62 | |
| ACM-SGC-12021.09 | 46.4 | |
| GCN2022.10 | 45.87 | |
| GCN2021.09 | 44.76 | |
| GAT*2021.09 | 42.72 | |
| SimP-GCN2023.12 | 42.57 | |
| FAGCN2021.09 | 42.24 | |
| GCNII2022.10 | 41.96 | |
| GraphSAGE2021.09 | 41.26 | |
| SGC-22021.09 | 41.25 | |
| ACM-SGC-22021.09 | 40.91 | |
| ACM-GCNII2021.09 | 40.9 | |
| ChebNetSplits=20 random 60%/20%/20% train/validation/test2022.10 | 40.81 | |
| H2GCN2021.09 | 38.85 | |
| GCNII2021.09 | 38.81 | |
| ACM-GCNII*2021.09 | 38.32 | |
| GCNII*2021.09 | 38.31 | |
| Geom-GCN2023.12 | 38.14 | |
| ARMASplits=20 random 60%/20%/20% train/validation/test2022.10 | 36.27 | |
| APPNPSplits=20 random 60%/20%/20% train/validation/test2022.10 | 35.71 | |
| APPNP*2021.09 | 34.77 | |
| UGCN2023.12 | 34.39 | |
| MLP-2*2021.09 | 31.28 | |
| MLP2022.10 | 31.01 | |
| H2GCN2022.10 | 30.39 | |
| MixHop2022.10 | 24.55 | |
| MixHop2021.09 | 24.55 |