Accuracy Prediction on NAS-Bench-201 8 (whole dataset)
0.901Kendall's TauNAR-Former
Evaluation Results
| Method | Links | |
|---|---|---|
| NAR-FormerBackbone=Transformer, Training Samples=10% (1563)2025.07 | 0.901 | |
| NN-FormerBackbone=Hybrid, Training Samples=10% (1563)2025.07 | 0.89 | |
| NAR-Former V2Backbone=Hybrid, Training Samples=10% (1563)2025.07 | 0.888 | |
| NN-FormerBackbone=Hybrid, Training Samples=5% (781)2025.07 | 0.879 | |
| NAR-Former V2Backbone=Hybrid, Training Samples=5% (781)2025.07 | 0.874 | |
| NN-FormerBackbone=Hybrid, Training Samples=3% (469)2025.07 | 0.86 | |
| NAR-FormerBackbone=Transformer, Training Samples=5% (781)2025.07 | 0.849 | |
| NAR-Former V2Backbone=Hybrid, Training Samples=3% (469)2025.07 | 0.846 | |
| NN-FormerBackbone=Hybrid, Training Samples=1% (156)2025.07 | 0.804 | |
| NAR-FormerBackbone=Transformer, Training Samples=3% (469)2025.07 | 0.79 | |
| PINATBackbone=Transformer, Training Samples=10% (1563)2025.07 | 0.784 | |
| GraphormerBackbone=Transformer, Training Samples=10% (1563)2025.07 | 0.776 | |
| PINATBackbone=Transformer, Training Samples=5% (781)2025.07 | 0.761 | |
| NAR-Former V2Backbone=Hybrid, Training Samples=1% (156)2025.07 | 0.752 | |
| TNASPBackbone=Transformer, Training Samples=10% (1563)2025.07 | 0.724 | |
| GraphormerBackbone=Transformer, Training Samples=5% (781)2025.07 | 0.719 | |
| PINATBackbone=Transformer, Training Samples=3% (469)2025.07 | 0.706 | |
| TNASPBackbone=Transformer, Training Samples=5% (781)2025.07 | 0.689 | |
| GraphormerBackbone=Transformer, Training Samples=3% (469)2025.07 | 0.68 | |
| GraphTransBackbone=Hybrid, Training Samples=10% (1563)2025.07 | 0.673 | |
| NAR-FormerBackbone=Transformer, Training Samples=1% (156)2025.07 | 0.66 | |
| NPBackbone=GNN, Training Samples=10% (1563)2025.07 | 0.646 | |
| TNASPBackbone=Transformer, Training Samples=3% (469)2025.07 | 0.64 | |
| NPBackbone=GNN, Training Samples=5% (781)2025.07 | 0.634 | |
| PINATBackbone=Transformer, Training Samples=1% (156)2025.07 | 0.631 | |
| GraphormerBackbone=Transformer, Training Samples=1% (156)2025.07 | 0.63 | |
| TNASPBackbone=Transformer, Training Samples=1% (156)2025.07 | 0.589 | |
| GraphTransBackbone=Hybrid, Training Samples=5% (781)2025.07 | 0.588 | |
| NPBackbone=GNN, Training Samples=3% (469)2025.07 | 0.584 | |
| GraphTransBackbone=Hybrid, Training Samples=3% (469)2025.07 | 0.55 | |
| NAOBackbone=LSTM, Training Samples=10% (1563)2025.07 | 0.526 | |
| NAOBackbone=LSTM, Training Samples=5% (781)2025.07 | 0.522 | |
| NAOBackbone=LSTM, Training Samples=1% (156)2025.07 | 0.493 | |
| NAOBackbone=LSTM, Training Samples=3% (469)2025.07 | 0.47 | |
| NPBackbone=GNN, Training Samples=1% (156)2025.07 | 0.413 | |
| GraphTransBackbone=Hybrid, Training Samples=1% (156)2025.07 | 0.409 |