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Node Classification On Minesweeper
Métriques
AUCROC
Résultats
Résultats de performance de divers modèles sur ce benchmark
| Paper Title | ||
|---|---|---|
| GCN | 97.86 ± 0.24 | Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification |
| GraphSAGE | 97.77 ± 0.62 | Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification |
| GAT | 97.73 ± 0.73 | Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification |
| Polynormer | 97.46±0.36 | Polynormer: Polynomial-Expressive Graph Transformer in Linear Time |
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