Node Classification on ACTIVSg 2000
89.06AccuracyTRI-GNND
Evaluation results
| Method | Links | ||
|---|---|---|---|
| TRI-GNNDfiltration function=node degree2021.10 | 89.06 | 0.44 | |
| TRI-GNNAfiltration function=node attributes2021.10 | 88.82 | 0.56 | |
| LFGCN2021.10 | 87.74 | 0.3 | |
| PEGN-RC2021.10 | 87.62 | 0.74 | |
| VPN2021.10 | 86.87 | 0.33 | |
| APPNP2021.10 | 86.77 | 0.3 | |
| GMNN2021.10 | 86.21 | 0.29 | |
| MixHop2021.10 | 86.1 | 0.25 | |
| SPAGAN2021.10 | 86 | 0.26 | |
| LGCNS2021.10 | 85.57 | 0.25 | |
| RGCN2021.10 | 85.23 | 0.4 | |
| GAT2021.10 | 83 | 0.59 | |
| MotifNet2021.10 | 82 | 0.44 | |
| ARMA2021.10 | 81.2 | 0.23 | |
| ChebNet2021.10 | 80.04 | 0.37 | |
| GCN2021.10 | 73.36 | 0.41 |