Accuracy Prediction on NAS-Bench-201 depth=8
0.947Kendall's TauNAR-Former
Evaluation Results
| Method | Links | |
|---|---|---|
| NAR-FormerBackbone=Transformer, Training Samples=50% (7812)2022.11 | 0.947 | |
| NAR-FormerBackbone=Transformer, Training Samples=10% (1563)2022.11 | 0.901 | |
| NAR-FormerBackbone=Transformer, Training Samples=5% (781)2022.11 | 0.849 | |
| TNASP + SEBackbone=Transformer, Training Samples=10% (1563)2022.11 | 0.726 | |
| TNASPBackbone=Transformer, Training Samples=10% (1563)2022.11 | 0.724 | |
| TNASP + SEBackbone=Transformer, Training Samples=5% (781)2022.11 | 0.69 | |
| TNASPBackbone=Transformer, Training Samples=5% (781)2022.11 | 0.689 | |
| NP + SEBackbone=GCN, Training Samples=5% (781)2022.11 | 0.652 | |
| NP + SEBackbone=GCN, Training Samples=10% (1563)2022.11 | 0.649 | |
| NPBackbone=GCN, Training Samples=10% (1563)2022.11 | 0.646 | |
| NPBackbone=GCN, Training Samples=5% (781)2022.11 | 0.634 | |
| NAO + SEBackbone=LSTM, Training Samples=5% (781)2022.11 | 0.529 | |
| NAO + SEBackbone=LSTM, Training Samples=10% (1563)2022.11 | 0.528 | |
| NAOBackbone=LSTM, Training Samples=10% (1563)2022.11 | 0.526 | |
| NAOBackbone=LSTM, Training Samples=5% (781)2022.11 | 0.522 |