Node Classification On Wiki Vote
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| DEMO-Net(weight) | 99.8 | DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification |
| GAT (Velickovic et al., 2018) | 59.4 | Graph Attention Networks |
| GCN_cheby (Kipf and Welling, 2017) | 49.5 | Semi-Supervised Classification with Graph Convolutional Networks |
| Union (Li et al., 2018) | 46.3 | Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning |
| GCN (Kipf and Welling, 2017) | 32.9 | Semi-Supervised Classification with Graph Convolutional Networks |
| GraphSAGE (Hamilton et al., [2017a]) | 24.5 | Inductive Representation Learning on Large Graphs |
0 of 6 row(s) selected.