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

Showing 476500 of 1915 papers

TitleStatusHype
CycleGANAS: Differentiable Neural Architecture Search for CycleGANCode0
Customized Subgraph Selection and Encoding for Drug-drug Interaction PredictionCode0
Long-term Reproducibility for Neural Architecture SearchCode0
CSCO: Connectivity Search of Convolutional OperatorsCode0
Auto-Keras: An Efficient Neural Architecture Search SystemCode0
Improving the sample-efficiency of neural architecture search with reinforcement learningCode0
Investigating the Impact of Hard Samples on Accuracy Reveals In-class Data ImbalanceCode0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NASCode0
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural NetworksCode0
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture SearchCode0
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation FusionCode0
ImmuNetNAS: An Immune-network approach for searching Convolutional Neural Network ArchitecturesCode0
Accelerating Neural Architecture Search using Performance PredictionCode0
Implantable Adaptive Cells: differentiable architecture search to improve the performance of any trained U-shaped networkCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
DetNAS: Backbone Search for Object DetectionCode0
Improved Differentiable Architecture Search for Language Modeling and Named Entity RecognitionCode0
Improving Neural Architecture Search by Mixing a FireFly algorithm with a Training Free EvaluationCode0
Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage DatasetCode0
Contrastive Self-supervised Neural Architecture SearchCode0
AutoGrow: Automatic Layer Growing in Deep Convolutional NetworksCode0
DFG-NAS: Deep and Flexible Graph Neural Architecture SearchCode0
Continuous Cartesian Genetic Programming based representation for Multi-Objective Neural Architecture SearchCode0
HYBRIDFORMER: improving SqueezeFormer with hybrid attention and NSR mechanismCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPOS (ProxylessNAS (GPU) latency)Accuracy75.3Unverified
2SPOS (FBNet-C latency)Accuracy75.1Unverified
3SPOS (block search + channel search)Accuracy74.7Unverified
4MUXNet-xsTop-1 Error Rate33.3Unverified
5FBNetV2-F1Top-1 Error Rate31.7Unverified
6LayerNAS-60MTop-1 Error Rate31Unverified
7NASGEPTop-1 Error Rate29.51Unverified
8MUXNet-sTop-1 Error Rate28.4Unverified
9NN-MASS-ATop-1 Error Rate27.1Unverified
10FBNetV2-F3Top-1 Error Rate26.8Unverified
#ModelMetricClaimedVerifiedStatus
1CR-LSOAccuracy (Test)46.98Unverified
2Shapley-NASAccuracy (Test)46.85Unverified
3β-RDARTS-L2Accuracy (Test)46.71Unverified
4β-SDARTS-RSAccuracy (Test)46.71Unverified
5ASE-NAS+Accuracy (Val)46.66Unverified
6NARAccuracy (Test)46.66Unverified
7BaLeNAS-TFAccuracy (Test)46.54Unverified
8AG-NetAccuracy (Test)46.42Unverified
9Local searchAccuracy (Test)46.38Unverified
10NASBOTAccuracy (Test)46.37Unverified
#ModelMetricClaimedVerifiedStatus
1Balanced MixtureAccuracy (% )91.55Unverified
2GDASTop-1 Error Rate3.4Unverified
3Bonsai-NetTop-1 Error Rate3.35Unverified
4Net2 (2)Top-1 Error Rate3.3Unverified
5μDARTSTop-1 Error Rate3.28Unverified
6NN-MASS- CIFAR-CTop-1 Error Rate3.18Unverified
7NN-MASS- CIFAR-ATop-1 Error Rate3Unverified
8DARTS (first order)Top-1 Error Rate3Unverified
9NASGEPTop-1 Error Rate2.82Unverified
10AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82Unverified