Neural Architecture Search

Neural architecture search (NAS) is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine learning. NAS essentially takes the process of a human manually tweaking a neural network and learning what works well, and automates this task to discover more complex architectures.

Image Credit : NAS with Reinforcement Learning

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 701–725 of 1915 papers

Title	Date	Tasks	Status	Score
Guided Evolution for Neural Architecture Search	Oct 28, 2021	Neural Architecture Search	CodeCode Available	5
NASH: Neural Architecture Search for Hardware-Optimized Machine Learning Models	Mar 4, 2024	Neural Architecture Search	CodeCode Available	5
EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching	Jul 20, 2022	GPUimage-classification	CodeCode Available	5
BASQ: Branch-wise Activation-clipping Search Quantization for Sub-4-bit Neural Networks	Oct 23, 2022	Neural Architecture SearchQuantization	CodeCode Available	5
Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start"	Feb 2, 2023	Neural Architecture Search	CodeCode Available	5
Architecture-Aware Minimization (A^2M): How to Find Flat Minima in Neural Architecture Search	Mar 13, 2025	Neural Architecture Search	CodeCode Available	5
Hierarchical Representations for Efficient Architecture Search	Nov 1, 2017	General Classificationimage-classification	CodeCode Available	5
Band-gap regression with architecture-optimized message-passing neural networks	Sep 12, 2023	Band Gapband gap regression	CodeCode Available	5
Exploring Randomly Wired Neural Networks for Image Recognition	Apr 2, 2019	Image ClassificationNeural Architecture Search	CodeCode Available	5
DVOLVER: Efficient Pareto-Optimal Neural Network Architecture Search	Feb 5, 2019	Neural Architecture Search	CodeCode Available	5
GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators	Jul 13, 2023	Drug DiscoveryGraph Embedding	CodeCode Available	5
Exploring Robust Architectures for Deep Artificial Neural Networks	Jun 30, 2021	AutoMLimage-classification	CodeCode Available	5
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs	Apr 24, 2019	Bayesian OptimizationBIG-bench Machine Learning	CodeCode Available	5
GradSign: Model Performance Inference with Theoretical Insights	Oct 16, 2021	modelNeural Architecture Search	CodeCode Available	5
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search	Jan 27, 2022	Neural Architecture Search	CodeCode Available	5
BAM: Bottleneck Attention Module	Jul 17, 2018	Neural Architecture Search	CodeCode Available	5
Auptimizer -- an Extensible, Open-Source Framework for Hyperparameter Tuning	Nov 6, 2019	ARCBIG-bench Machine Learning	CodeCode Available	5
GraphNAS: Graph Neural Architecture Search with Reinforcement Learning	Apr 22, 2019	General ClassificationInductive Learning	CodeCode Available	5
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy	Oct 16, 2021	Deep LearningNeural Architecture Search	CodeCode Available	5
Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search	Nov 27, 2019	AutoMLNeural Architecture Search	CodeCode Available	5
Gibbs randomness-compression proposition: An efficient deep learning	May 29, 2025	Deep LearningNeural Architecture Search	CodeCode Available	5
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search	Jul 3, 2019	FairnessImage Classification	CodeCode Available	5
ABC-Di: Approximate Bayesian Computation for Discrete Data	Oct 19, 2020	Neural Architecture Searchvalid	CodeCode Available	5
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks	May 23, 2023	Neural Architecture Search	CodeCode Available	5
Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture	Jun 21, 2023	Image ClassificationNeural Architecture Search	CodeCode Available	5

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All datasets ImageNet NAS-Bench-201, ImageNet-16-120 CIFAR-10 NAS-Bench-201, CIFAR-100 NAS-Bench-201, CIFAR-10 CIFAR-10 Image Classification CIFAR-100 NATS-Bench Topology, CIFAR-10 NATS-Bench Topology, CIFAR-100 NATS-Bench Topology, ImageNet16-120 Food-101 NAS-Bench-101

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SPOS (ProxylessNAS (GPU) latency)	Accuracy	75.3	—	Unverified
2	SPOS (FBNet-C latency)	Accuracy	75.1	—	Unverified
3	SPOS (block search + channel search)	Accuracy	74.7	—	Unverified
4	MUXNet-xs	Top-1 Error Rate	33.3	—	Unverified
5	FBNetV2-F1	Top-1 Error Rate	31.7	—	Unverified
6	LayerNAS-60M	Top-1 Error Rate	31	—	Unverified
7	NASGEP	Top-1 Error Rate	29.51	—	Unverified
8	MUXNet-s	Top-1 Error Rate	28.4	—	Unverified
9	NN-MASS-A	Top-1 Error Rate	27.1	—	Unverified
10	FBNetV2-F3	Top-1 Error Rate	26.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CR-LSO	Accuracy (Test)	46.98	—	Unverified
2	Shapley-NAS	Accuracy (Test)	46.85	—	Unverified
3	β-RDARTS-L2	Accuracy (Test)	46.71	—	Unverified
4	β-SDARTS-RS	Accuracy (Test)	46.71	—	Unverified
5	ASE-NAS+	Accuracy (Val)	46.66	—	Unverified
6	NAR	Accuracy (Test)	46.66	—	Unverified
7	BaLeNAS-TF	Accuracy (Test)	46.54	—	Unverified
8	AG-Net	Accuracy (Test)	46.42	—	Unverified
9	Local search	Accuracy (Test)	46.38	—	Unverified
10	NASBOT	Accuracy (Test)	46.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Balanced Mixture	Accuracy (% )	91.55	—	Unverified
2	GDAS	Top-1 Error Rate	3.4	—	Unverified
3	Bonsai-Net	Top-1 Error Rate	3.35	—	Unverified
4	Net2 (2)	Top-1 Error Rate	3.3	—	Unverified
5	μDARTS	Top-1 Error Rate	3.28	—	Unverified
6	NN-MASS- CIFAR-C	Top-1 Error Rate	3.18	—	Unverified
7	NN-MASS- CIFAR-A	Top-1 Error Rate	3	—	Unverified
8	DARTS (first order)	Top-1 Error Rate	3	—	Unverified
9	NASGEP	Top-1 Error Rate	2.82	—	Unverified
10	AlphaX-1 (cutout NASNet)	Top-1 Error Rate	2.82	—	Unverified