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 1801–1825 of 1915 papers

Title	Date	Tasks	Status
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures	Apr 3, 2017	General Classificationimage-classification	CodeCode Available
Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters	Oct 25, 2019	Neural Architecture Search	CodeCode Available
A Transformer-based Neural Architecture Search Method	May 2, 2025	DecoderNeural Architecture Search	CodeCode Available
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy	Oct 16, 2021	Deep LearningNeural Architecture Search	CodeCode Available
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets	Apr 15, 2022	Image RetrievalNeural Architecture Search	CodeCode Available
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?	Apr 8, 2019	Neural Architecture SearchReinforcement Learning	CodeCode Available
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks	May 23, 2023	Neural Architecture Search	CodeCode Available
Resource-efficient DNNs for Keyword Spotting using Neural Architecture Search and Quantization	Dec 18, 2020	Keyword SpottingNeural Architecture Search	CodeCode Available
Seesaw-Net: Convolution Neural Network With Uneven Group Convolution	May 9, 2019	image-classificationImage Classification	CodeCode Available
Hierarchical Neural Architecture Search via Operator Clustering	Sep 26, 2019	ClusteringNeural Architecture Search	CodeCode Available
Distilled Pruning: Using Synthetic Data to Win the Lottery	Jul 7, 2023	Efficient Neural NetworkModel Compression	CodeCode Available
DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation	Mar 29, 2021	GPUImage Segmentation	CodeCode Available
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and L_0 Regularization	Dec 7, 2020	Image ClassificationModel Selection	CodeCode Available
Differentially-private Federated Neural Architecture Search	Jun 16, 2020	Neural Architecture Search	CodeCode Available
Rethink DARTS Search Space and Renovate a New Benchmark	Jun 12, 2023	Neural Architecture Search	CodeCode Available
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance	Aug 16, 2024	Neural Architecture Search	CodeCode Available
BATS: Binary ArchitecTure Search	Mar 3, 2020	BinarizationClassification with Binary Neural Network	CodeCode Available
BatchQuant: Quantized-for-all Architecture Search with Robust Quantizer	May 19, 2021	AllGPU	CodeCode Available
BASQ: Branch-wise Activation-clipping Search Quantization for Sub-4-bit Neural Networks	Oct 23, 2022	Neural Architecture SearchQuantization	CodeCode Available
Band-gap regression with architecture-optimized message-passing neural networks	Sep 12, 2023	Band Gapband gap regression	CodeCode Available
Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start	Jul 17, 2020	GPUNeural Architecture Search	CodeCode Available
BAM: Bottleneck Attention Module	Jul 17, 2018	Neural Architecture Search	CodeCode Available
Network Pruning via Transformable Architecture Search	May 23, 2019	Knowledge DistillationNetwork Pruning	CodeCode Available
Efficient Neural Architecture Search via Proximal Iterations	May 30, 2019	GPUNeural Architecture Search	CodeCode Available
Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture	Jun 21, 2023	Image ClassificationNeural Architecture Search	CodeCode Available

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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