Node Classification On Minesweeper
Metriken
AUCROC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | AUCROC | Paper Title | Repository |
|---|---|---|---|
| GAT | 97.73 ± 0.73 | 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 | |
| Polynormer | 97.46±0.36 | Polynormer: Polynomial-Expressive Graph Transformer in Linear Time | |
| GCN | 97.86 ± 0.24 | Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification |
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