Neural Architecture Search On Nas Bench 201 1

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Accuracy (Test)

Accuracy (Val)

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Accuracy (Test)	Accuracy (Val)	Paper Title	Repository
NAR	94.33	91.44	Generalized Global Ranking-Aware Neural Architecture Ranker for Efficient Image Classifier Search
β-DARTS	94.36	91.55	$β$-DARTS: Beta-Decay Regularization for Differentiable Architecture Search
DARTS-V2	54.30	39.77	-	-
GDAS	93.61	89.89	Searching for A Robust Neural Architecture in Four GPU Hours
arch2vec	94.18	91.41	Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
EPE-NAS (N=10)	92.63	89.90	EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search
SNAS	92.77	90.10	SNAS: Stochastic Neural Architecture Search
Shapley-NAS	94.37	91.61	Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search
DARTS-	93.80	91.03	DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
SETN	86.19	82.25	-	-
DARTS-V1	54.30	39.77	-	-
NAS-LID+RSPS	92.9	89.74	NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
DU-DARTS	93.86	91.21	DU-DARTS: Decreasing the Uncertainty of Differentiable Architecture Search
AG-Net	94.37	91.61	Learning Where To Look -- Generative NAS is Surprisingly Efficient
BaLeNAS-TF	94.33	91.52	BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule	-
Λ-DARTS	94.36	91.55	$Λ$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells
GAEA DARTS (ERM)	94.1	-	Geometry-Aware Gradient Algorithms for Neural Architecture Search
RSPS	87.66	84.16	Random Search and Reproducibility for Neural Architecture Search
IS-DARTS	94.36	91.55	IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance
CATCH-meta	-	91.33	CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search	-

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