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Neural Architecture Search On Nats Bench

Metrics

Test Accuracy

Results

Performance results of various models on this benchmark

Model Name
Test Accuracy
Paper TitleRepository
EigenNas (Zhu et al., 2022)45.54Generalization Properties of NAS under Activation and Skip Connection Search-
LayerNAS46.58±0.59LayerNAS: Neural Architecture Search in Polynomial Complexity-
GreenMachine-2-GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS-
FairNAS (Chu et al., 2021)42.19FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search-
GreenMachine-3-GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS-
TE-NAS (Chen et al., 2021)42.38Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective-
NASI (Shu et al., 2021)44.84NASI: Label- and Data-agnostic Neural Architecture Search at Initialization-
GreenMachine-1-GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS-
KNAS (Xu et al., 2021)34.11KNAS: Green Neural Architecture Search-
RE (Real et al., 2019)44.76Regularized Evolution for Image Classifier Architecture Search-
PPO (Schulman et al., 2017)44.95Proximal Policy Optimization Algorithms-
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