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 801–825 of 1915 papers

Title	Date	Tasks	Status	Score
Heterogeneous Graph Neural Architecture Search with GPT-4	Dec 14, 2023	Neural Architecture Search	CodeCode Available	5
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost	May 9, 2024	Auxiliary LearningNeural Architecture Search	CodeCode Available	5
Hardware Aware Neural Network Architectures using FbNet	Jun 17, 2019	BenchmarkingNeural Architecture Search	CodeCode Available	5
DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation	Mar 29, 2021	GPUImage Segmentation	CodeCode Available	5
A Classification of G-invariant Shallow Neural Networks	May 18, 2022	General ClassificationNeural Architecture Search	CodeCode Available	5
Hardware/Software Co-Exploration of Neural Architectures	Jul 6, 2019	Neural Architecture SearchReinforcement Learning	CodeCode Available	5
How to 0wn the NAS in Your Spare Time	May 1, 2020	CPUMalware Detection	CodeCode Available	5
Auto-tuning of Deep Neural Networks by Conflicting Layer Removal	Mar 7, 2021	Neural Architecture Search	CodeCode Available	5
Autoequivariant Network Search via Group Decomposition	Apr 10, 2021	Inductive BiasNeural Architecture Search	CodeCode Available	5
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and L_0 Regularization	Dec 7, 2020	Image ClassificationModel Selection	CodeCode Available	5
Differentially-private Federated Neural Architecture Search	Jun 16, 2020	Neural Architecture Search	CodeCode Available	5
Guided Evolution for Neural Architecture Search	Oct 28, 2021	Neural Architecture Search	CodeCode Available	5
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data	Dec 17, 2019	Neural Architecture SearchReinforcement Learning	CodeCode Available	5
Efficient Neural Architecture Search via Proximal Iterations	May 30, 2019	GPUNeural Architecture Search	CodeCode Available	5
Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement	Dec 1, 2020	Bilevel OptimizationNeural Architecture Search	CodeCode Available	5
EENA: Efficient Evolution of Neural Architecture	May 10, 2019	General ClassificationGPU	CodeCode Available	5
GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS	Nov 22, 2024	Neural Architecture Search	CodeCode Available	5
Language Models with Transformers	Apr 20, 2019	Computational EfficiencyLanguage Modeling	CodeCode Available	5
GradSign: Model Performance Inference with Theoretical Insights	Oct 16, 2021	modelNeural Architecture Search	CodeCode Available	5
Gibbs randomness-compression proposition: An efficient deep learning	May 29, 2025	Deep LearningNeural Architecture Search	CodeCode Available	5
AutoST: Training-free Neural Architecture Search for Spiking Transformers	Jul 1, 2023	Neural Architecture Search	CodeCode Available	5
Self-supervised Representation Learning for Evolutionary Neural Architecture Search	Oct 31, 2020	Contrastive LearningGraph Neural Network	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
GraphNAS: Graph Neural Architecture Search with Reinforcement Learning	Apr 22, 2019	General ClassificationInductive Learning	CodeCode Available	5
Differentiable NAS Framework and Application to Ads CTR Prediction	Oct 25, 2021	Click-Through Rate PredictionNeural 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