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 51–100 of 1915 papers

TitleStatusHype
Accelerating Neural Architecture Search via Proxy DataCode1
Automated Machine Learning on Graphs: A SurveyCode1
Discovering Neural WiringsCode1
Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT ScansCode1
Automatic Relation-aware Graph Network ProliferationCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
Cyclic Differentiable Architecture SearchCode1
Deep Multimodal Neural Architecture SearchCode1
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine TranslationCode1
AutoML: A Survey of the State-of-the-ArtCode1
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture SearchCode1
Designing the Topology of Graph Neural Networks: A Novel Feature Fusion PerspectiveCode1
DataDAM: Efficient Dataset Distillation with Attention MatchingCode1
Dataset Condensation with Gradient MatchingCode1
Differential Evolution for Neural Architecture SearchCode1
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free GrammarsCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
Contrastive Embeddings for Neural ArchitecturesCode1
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural NetworksCode1
Aligned Structured Sparsity Learning for Efficient Image Super-ResolutionCode1
ColdNAS: Search to Modulate for User Cold-Start RecommendationCode1
Contrastive Neural Architecture Search with Neural Architecture ComparatorsCode1
ChamNet: Towards Efficient Network Design through Platform-Aware Model AdaptationCode1
Can GPT-4 Perform Neural Architecture Search?Code1
CLEARER: Multi-Scale Neural Architecture Search for Image RestorationCode1
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network QuantizationCode1
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed SpacesCode1
AutoKE: An automatic knowledge embedding framework for scientific machine learningCode1
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum SearchCode1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D NetworksCode1
AtomNAS: Fine-Grained End-to-End Neural Architecture SearchCode1
AttentiveNAS: Improving Neural Architecture Search via Attentive SamplingCode1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-IdentificationCode1
Canvas: End-to-End Kernel Architecture Search in Neural NetworksCode1
CATE: Computation-aware Neural Architecture Encoding with TransformersCode1
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity EvaluationCode1
AutoGL: A Library for Automated Graph LearningCode1
AlphaNet: Improved Training of Supernets with Alpha-DivergenceCode1
Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree SearchCode1
Block-Wisely Supervised Neural Architecture Search With Knowledge DistillationCode1
Adaptive Cross-Layer Attention for Image RestorationCode1
BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image SegmentationCode1
Blockwisely Supervised Neural Architecture Search with Knowledge DistillationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
A Study on Encodings for Neural Architecture SearchCode1
Automated Concatenation of Embeddings for Structured PredictionCode1
Adaptive Linear Span Network for Object Skeleton DetectionCode1
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage ModelsCode1
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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-RDARTS-L2Accuracy (Test)46.71—Unverified
4β-SDARTS-RSAccuracy (Test)46.71—Unverified
5ASE-NAS+Accuracy (Val)46.66—Unverified
6NARAccuracy (Test)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
7NN-MASS- CIFAR-ATop-1 Error Rate3—Unverified
8DARTS (first order)Top-1 Error Rate3—Unverified
9NASGEPTop-1 Error Rate2.82—Unverified
10AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82—Unverified