Node Classification on PubMed (standard fixed split)
80.4AccuracyMTGAE
Evaluation Results
| Method | Links | |
|---|---|---|
| MTGAEscenario=MTL (Multi-Task Learning)2018.11 | 80.4 | |
| AGNNInput=YL, X, G2018.03 | 79.9 | |
| N-GCN2018.09 | 79.4 | |
| GPNN2018.09 | 79.3 | |
| DynamicFilterInput=YL, X, G2018.03 | 79 | |
| GCNInput=YL, X, G2018.03 | 79 | |
| GCN2018.09 | 79 | |
| FeaStNet2018.09 | 79 | |
| GAT2018.09 | 79 | |
| GCNscenario=task-specific2018.11 | 79 | |
| GLNInput=YL, X, G2018.03 | 78.9 | |
| SEGCN2018.09 | 78.9 | |
| MoNetInput=YL, X, G2018.03 | 78.8 | |
| BootstrapInput=YL, X, G2018.03 | 78.8 | |
| MoNet2018.09 | 78.8 | |
| Bootstrap2018.09 | 78.8 | |
| GCN*implementation=own implementation2018.09 | 78.6 | |
| PlanetoidInput=YL, X, G2018.03 | 77.2 | |
| Planetoid2018.09 | 77.2 | |
| Planetoidscenario=task-specific2018.11 | 77.2 | |
| node2vecInput=YL, G2018.03 | 75.3 | |
| node2vec2018.09 | 75.3 | |
| ICAInput=YL, X, G2018.03 | 73.9 | |
| DCNNInput=YL, X, G2018.03 | 73 | |
| DCNN2018.09 | 73 | |
| Multilayer PerceptronInput=YL, XL2018.03 | 71.4 | |
| SemiEmbInput=YL, X, G2018.03 | 71.1 | |
| ManiRegInput=YL, X, G2018.03 | 70.7 | |
| Singlelayer PerceptronInput=YL, XL2018.03 | 69.8 | |
| DeepWalkInput=YL, G2018.03 | 65.3 | |
| DeepWalk2018.09 | 65.3 | |
| LPInput=YL, X, G2018.03 | 63 | |
| T-SVMInput=YL, X2018.03 | 62.2 |