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

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Showing 101–150 of 1915 papers

TitleStatusHype
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
Hyper-Representations as Generative Models: Sampling Unseen Neural Network WeightsCode1
On the Privacy Risks of Cell-Based NAS ArchitecturesCode1
You Only Search Once: On Lightweight Differentiable Architecture Search for Resource-Constrained Embedded PlatformsCode1
SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture SearchCode1
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture SearchCode1
Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance AssessmentCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
Hyper-Representations for Pre-Training and Transfer LearningCode1
DC-BENCH: Dataset Condensation BenchmarkCode1
NASRec: Weight Sharing Neural Architecture Search for Recommender SystemsCode1
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture SearchCode1
UniNet: Unified Architecture Search with Convolution, Transformer, and MLPCode1
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter PruningCode1
FlowNAS: Neural Architecture Search for Optical Flow EstimationCode1
Multi-Prior Learning via Neural Architecture Search for Blind Face RestorationCode1
Prior-Guided One-shot Neural Architecture SearchCode1
Shapley-NAS: Discovering Operation Contribution for Neural Architecture SearchCode1
NAS-Bench-Graph: Benchmarking Graph Neural Architecture SearchCode1
FreeREA: Training-Free Evolution-based Architecture SearchCode1
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural ReparameterizationCode1
Automatic Relation-aware Graph Network ProliferationCode1
AutoKE: An automatic knowledge embedding framework for scientific machine learningCode1
Efficient Architecture Search for Diverse TasksCode1
Generalizing Few-Shot NAS with Gradient MatchingCode1
Q-PPG: Energy-Efficient PPG-based Heart Rate Monitoring on Wearable DevicesCode1
PACE: A Parallelizable Computation Encoder for Directed Acyclic GraphsCode1
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot LearningCode1
DATA: Domain-Aware and Task-Aware Self-supervised LearningCode1
Learning Where To Look -- Generative NAS is Surprisingly EfficientCode1
Towards Less Constrained Macro-Neural Architecture SearchCode1
Evolutionary Neural Cascade Search across SupernetworksCode1
Adaptive Cross-Layer Attention for Image RestorationCode1
β-DARTS: Beta-Decay Regularization for Differentiable Architecture SearchCode1
PaSca: a Graph Neural Architecture Search System under the Scalable ParadigmCode1
Bayesian Model Selection, the Marginal Likelihood, and GeneralizationCode1
AutoSNN: Towards Energy-Efficient Spiking Neural NetworksCode1
Generalized Global Ranking-Aware Neural Architecture Ranker for Efficient Image Classifier SearchCode1
Neural Architecture Search for Spiking Neural NetworksCode1
NAS-VAD: Neural Architecture Search for Voice Activity DetectionCode1
Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and DirectionsCode1
b-DARTS: Beta-Decay Regularization for Differentiable Architecture SearchCode1
Designing the Topology of Graph Neural Networks: A Novel Feature Fusion PerspectiveCode1
Scale-Aware Neural Architecture Search for Multivariate Time Series ForecastingCode1
Aligned Structured Sparsity Learning for Efficient Image Super-ResolutionCode1
Hardware-adaptive Efficient Latency Prediction for NAS via Meta-LearningCode1
EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANsCode1
Searching the Search Space of Vision TransformerCode1
TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather ConditionsCode1
ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image PriorCode1
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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