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Neural Architecture Search On Nats Bench

Metrics

Test Accuracy

Results

Performance results of various models on this benchmark

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