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ResearchFormerly WizWand

Accuracy Prediction on NAS-Bench-201 depth=8

0.947Kendall's TauNAR-Former
0.5050.619750.73450.84925Nov 15, 2022
Updated 8mo ago

Evaluation results

MethodLinks
NAR-FormerBackbone=Transformer, Training Samples=50% (7812)2022.110.947
NAR-FormerBackbone=Transformer, Training Samples=10% (1563)2022.110.901
NAR-FormerBackbone=Transformer, Training Samples=5% (781)2022.110.849
TNASP + SEBackbone=Transformer, Training Samples=10% (1563)2022.110.726
TNASPBackbone=Transformer, Training Samples=10% (1563)2022.110.724
TNASP + SEBackbone=Transformer, Training Samples=5% (781)2022.110.69
TNASPBackbone=Transformer, Training Samples=5% (781)2022.110.689
NP + SEBackbone=GCN, Training Samples=5% (781)2022.110.652
NP + SEBackbone=GCN, Training Samples=10% (1563)2022.110.649
NPBackbone=GCN, Training Samples=10% (1563)2022.110.646
NPBackbone=GCN, Training Samples=5% (781)2022.110.634
NAO + SEBackbone=LSTM, Training Samples=5% (781)2022.110.529
NAO + SEBackbone=LSTM, Training Samples=10% (1563)2022.110.528
NAOBackbone=LSTM, Training Samples=10% (1563)2022.110.526
NAOBackbone=LSTM, Training Samples=5% (781)2022.110.522