Neural Architecture Search On Nas Bench 201 2

Métriques

Accuracy (Test)

Accuracy (Val)

Search time (s)

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy (Test)	Accuracy (Val)	Search time (s)	Paper Title	Repository
DARTS-V1	15.61	15.03	10890	-	-
KNAS (k=40)	71.05	-	-	KNAS: Green Neural Architecture Search
DSNAS	-	31.01	-	DSNAS: Direct Neural Architecture Search without Parameter Retraining
SETN	56.87	59.05	31010	One-Shot Neural Architecture Search via Self-Evaluated Template Network
Shapley-NAS	73.51	73.49	-	Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search
IS-DARTS	73.51	73.49	-	IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance
RF-DARTS	72.94	72.95	-	Differentiable Architecture Search with Random Features	-
α-DARTS	73.16	73.21	-	$α$ DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling	-
SNAS	69.34	69.69	-	SNAS: Stochastic Neural Architecture Search
DARTS-V2	15.61	15.03	29902	-	-
iDARTS	70.83	70.57	-	iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
DrNAS	73.51	73.49	-	DrNAS: Dirichlet Neural Architecture Search
GAEA DARTS (ERM)	73.43	-	-	Geometry-Aware Gradient Algorithms for Neural Architecture Search
ENAS	15.61	15.03	13315	Efficient Neural Architecture Search via Parameters Sharing	-
BaLeNAS-TF	72.95	72.67	-	BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule	-
GenNAS	72.56	-	1080	Generic Neural Architecture Search via Regression
DiNAS	73.51	73.49	15.36	Multi-conditioned Graph Diffusion for Neural Architecture Search
arch2vec	73.37	73.35	-	Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
CR-LSO	73.47	73.44	-	CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks
DARTS-	71.53	71.36	-	DARTS-: Robustly Stepping out of Performance Collapse Without Indicators

0 of 40 row(s) selected.