SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1751–1800 of 1915 papers

TitleStatusHype
Efficient Multiplayer Battle Game Optimizer for Adversarial Robust Neural Architecture SearchCode0
Multi-scale Attentive Image De-raining Networks via Neural Architecture SearchCode0
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture SearchCode0
BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture SearchCode0
Recovering Quantitative Models of Human Information Processing with Differentiable Architecture SearchCode0
Auptimizer -- an Extensible, Open-Source Framework for Hyperparameter TuningCode0
Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT ClassificationCode0
NAAP-440 Dataset and Baseline for Neural Architecture Accuracy PredictionCode0
NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural NetworksCode0
AGNAS: Attention-Guided Micro- and Macro-Architecture SearchCode0
SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free MetricsCode0
NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid NetworksCode0
U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture SearchCode0
Efficient Incorporation of Multiple Latency Targets in the Once-For-All NetworkCode0
Efficient hyperparameter optimization by way of PAC-Bayes bound minimizationCode0
Efficient Global Neural Architecture SearchCode0
Efficient Decoupled Neural Architecture Search by Structure and Operation SamplingCode0
Efficient Architecture Search by Network TransformationCode0
Behaviour DistillationCode0
Efficient and Explainable Graph Neural Architecture Search via Monte-Carlo Tree SearchCode0
Efficacy of Neural Prediction-Based Zero-Shot NASCode0
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NASCode0
Regularized Evolution for Image Classifier Architecture SearchCode0
ECToNAS: Evolutionary Cross-Topology Neural Architecture SearchCode0
SpineNet: Learning Scale-Permuted Backbone for Recognition and LocalizationCode0
You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse OptimizationCode0
Reinforced Evolutionary Neural Architecture SearchCode0
EAT-NAS: Elastic Architecture Transfer for Accelerating Large-scale Neural Architecture SearchCode0
SP-NAS: Serial-to-Parallel Backbone Search for Object DetectionCode0
NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule NetworksCode0
SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different LanguagesCode0
EASNet: Searching Elastic and Accurate Network Architecture for Stereo MatchingCode0
NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture SearchCode0
NAS evaluation is frustratingly hardCode0
Bayesian Neural Network Language Modeling for Speech RecognitionCode0
Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start"Code0
DVOLVER: Efficient Pareto-Optimal Neural Network Architecture SearchCode0
Meta Architecture SearchCode0
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object DetectionCode0
Accelerating Neural Architecture Search using Performance PredictionCode0
ReNAS: Relativistic Evaluation of Neural Architecture SearchCode0
NASH: Neural Architecture and Accelerator Search for Multiplication-Reduced Hybrid ModelsCode0
NASH: Neural Architecture Search for Hardware-Optimized Machine Learning ModelsCode0
D-VAE: A Variational Autoencoder for Directed Acyclic GraphsCode0
NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese NetworksCode0
Bayesian Learning of Neural Network ArchitecturesCode0
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network ArchitectureCode0
SqueezeNAS: Fast neural architecture search for faster semantic segmentationCode0
SSHNN: Semi-Supervised Hybrid NAS Network for Echocardiographic Image SegmentationCode0
DropNAS: Grouped Operation Dropout for Differentiable Architecture SearchCode0
Show:102550
← PrevPage 36 of 39Next →
All datasetsImageNetNAS-Bench-201, ImageNet-16-120CIFAR-10NAS-Bench-201, CIFAR-100NAS-Bench-201, CIFAR-10CIFAR-10 Image ClassificationCIFAR-100NATS-Bench Topology, CIFAR-10NATS-Bench Topology, CIFAR-100NATS-Bench Topology, ImageNet16-120Food-101NAS-Bench-101

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPOS (ProxylessNAS (GPU) latency)Accuracy75.3—Unverified
2SPOS (FBNet-C latency)Accuracy75.1—Unverified
3SPOS (block search + channel search)Accuracy74.7—Unverified
4MUXNet-xsTop-1 Error Rate33.3—Unverified
5FBNetV2-F1Top-1 Error Rate31.7—Unverified
6LayerNAS-60MTop-1 Error Rate31—Unverified
7NASGEPTop-1 Error Rate29.51—Unverified
8MUXNet-sTop-1 Error Rate28.4—Unverified
9NN-MASS-ATop-1 Error Rate27.1—Unverified
10FBNetV2-F3Top-1 Error Rate26.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CR-LSOAccuracy (Test)46.98—Unverified
2Shapley-NASAccuracy (Test)46.85—Unverified
3β-SDARTS-RSAccuracy (Test)46.71—Unverified
4β-RDARTS-L2Accuracy (Test)46.71—Unverified
5NARAccuracy (Test)46.66—Unverified
6ASE-NAS+Accuracy (Val)46.66—Unverified
7BaLeNAS-TFAccuracy (Test)46.54—Unverified
8AG-NetAccuracy (Test)46.42—Unverified
9Local searchAccuracy (Test)46.38—Unverified
10NASBOTAccuracy (Test)46.37—Unverified
#ModelMetricClaimedVerifiedStatus
1Balanced MixtureAccuracy (% )91.55—Unverified
2GDASTop-1 Error Rate3.4—Unverified
3Bonsai-NetTop-1 Error Rate3.35—Unverified
4Net2 (2)Top-1 Error Rate3.3—Unverified
5μDARTSTop-1 Error Rate3.28—Unverified
6NN-MASS- CIFAR-CTop-1 Error Rate3.18—Unverified
7DARTS (first order)Top-1 Error Rate3—Unverified
8NN-MASS- CIFAR-ATop-1 Error Rate3—Unverified
9AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82—Unverified
10NASGEPTop-1 Error Rate2.82—Unverified