Node Classification On Flickr
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy |
|---|---|
| data-augmentation-for-graph-neural-networks | 0.682 |
| semi-supervised-classification-with-graph | 0.479 |
| inductive-representation-learning-on-large | 0.641 |
| a-comprehensive-study-on-large-scale-graph | 0.562 |
| demo-net-degree-specific-graph-neural | 0.656 ± 0.000 |
| semi-supervised-classification-with-graph | 0.546 |
| graph-attention-networks | 0.359 |
| deeper-insights-into-graph-convolutional | 0.557 |