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 376–400 of 1915 papers

Title	Date	Tasks	Status	Hype
SSHNN: Semi-Supervised Hybrid NAS Network for Echocardiographic Image Segmentation	Sep 9, 2023	DecoderImage Segmentation	CodeCode Available	0
DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation	Sep 7, 2023	BenchmarkingNeural Architecture Search	—Unverified	0
Efficacy of Neural Prediction-Based Zero-Shot NAS	Aug 31, 2023	Neural Architecture SearchPrediction	CodeCode Available	0
Efficient and Explainable Graph Neural Architecture Search via Monte-Carlo Tree Search	Aug 30, 2023	Neural Architecture Search	CodeCode Available	0
InstaTune: Instantaneous Neural Architecture Search During Fine-Tuning	Aug 29, 2023	Neural Architecture Search	—Unverified	0
Generalizable Learning Reconstruction for Accelerating MR Imaging via Federated Neural Architecture Search	Aug 27, 2023	Efficient Neural NetworkFairness	CodeCode Available	0
HNAS-reg: hierarchical neural architecture search for deformable medical image registration	Aug 23, 2023	Deep LearningDeformable Medical Image Registration	—Unverified	0
A Benchmark Study on Calibration	Aug 23, 2023	Neural Architecture Search	—Unverified	0
EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning	Aug 19, 2023	Generative Adversarial NetworkNeural Architecture Search	—Unverified	0
ResBuilder: Automated Learning of Depth with Residual Structures	Aug 16, 2023	Fraud Detectionimage-classification	—Unverified	0
Asynchronous Evolution of Deep Neural Network Architectures	Aug 8, 2023	Evolutionary AlgorithmsImage Captioning	—Unverified	0
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic Classification	Aug 4, 2023	ClassificationEarly Classification	CodeCode Available	1
Efficient Model Adaptation for Continual Learning at the Edge	Aug 3, 2023	AutoMLContinual Learning	—Unverified	0
Shrink-Perturb Improves Architecture Mixing during Population Based Training for Neural Architecture Search	Jul 28, 2023	Hyperparameter OptimizationImage Generation	CodeCode Available	0
YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems	Jul 26, 2023	BenchmarkingCPU	CodeCode Available	0
FedAutoMRI: Federated Neural Architecture Search for MR Image Reconstruction	Jul 21, 2023	Federated LearningImage Reconstruction	—Unverified	0
Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search	Jul 19, 2023	Decision MakingDrug Discovery	CodeCode Available	1
A Survey on Multi-Objective Neural Architecture Search	Jul 18, 2023	AutoMLHyperparameter Optimization	—Unverified	0
ShiftNAS: Improving One-shot NAS via Probability Shift	Jul 17, 2023	AttributeNeural Architecture Search	CodeCode Available	0
A Survey of Techniques for Optimizing Transformer Inference	Jul 16, 2023	Knowledge DistillationNeural Architecture Search	—Unverified	0
MaGNAS: A Mapping-Aware Graph Neural Architecture Search Framework for Heterogeneous MPSoC Deployment	Jul 16, 2023	GPUGraph Learning	—Unverified	0
GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators	Jul 13, 2023	Drug DiscoveryGraph Embedding	CodeCode Available	0
DDNAS: Discretized Differentiable Neural Architecture Search for Text Classification	Jul 12, 2023	ClassificationNeural Architecture Search	CodeCode Available	0
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Search	Jul 10, 2023	cognitive diagnosisNeural Architecture Search	CodeCode Available	1
Search-time Efficient Device Constraints-Aware Neural Architecture Search	Jul 10, 2023	Edge-computingimage-classification	—Unverified	0

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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