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