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 526–550 of 1915 papers

TitleStatusHype
EnTranNAS: Towards Closing the Gap between the Architectures in Search and Evaluation—0
Entropy-Driven Mixed-Precision Quantization for Deep Network Design—0
EPIM: Efficient Processing-In-Memory Accelerators based on Epitome—0
ERNAS: An Evolutionary Neural Architecture Search for Magnetic Resonance Image Reconstructions—0
CrossNAS: A Cross-Layer Neural Architecture Search Framework for PIM Systems—0
AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family—0
Adaptive Neural Networks Using Residual Fitting—0
Enhancing Convolutional Neural Networks with Higher-Order Numerical Difference Methods—0
CP-NAS: Child-Parent Neural Architecture Search for Binary Neural Networks—0
CP-CNN: Core-Periphery Principle Guided Convolutional Neural Network—0
AutoHR: A Strong End-to-end Baseline for Remote Heart Rate Measurement with Neural Searching—0
Core-set Sampling for Efficient Neural Architecture Search—0
Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs—0
Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach—0
Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures—0
AutoHAS: Efficient Hyperparameter and Architecture Search—0
AMLA: an AutoML frAmework for Neural Network Design—0
A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting—0
Enhanced Gradient for Differentiable Architecture Search—0
Continuous Ant-Based Neural Topology Search—0
Auto-GNN: Neural Architecture Search of Graph Neural Networks—0
Continual Segment: Towards a Single, Unified and Non-forgetting Continual Segmentation Model of 143 Whole-body Organs in CT Scans—0
Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans—0
Accelerating Neural Architecture Exploration Across Modalities Using Genetic Algorithms—0
Enhanced MRI Reconstruction Network using Neural Architecture Search—0
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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