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 251300 of 1915 papers

TitleStatusHype
Extensible Proxy for Efficient NASCode1
Searching a Compact Architecture for Robust Multi-Exposure Image FusionCode1
AutoSNN: Towards Energy-Efficient Spiking Neural NetworksCode1
Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity MaximizationCode1
FEAR: A Simple Lightweight Method to Rank ArchitecturesCode1
Equivalence in Deep Neural Networks via Conjugate Matrix EnsemblesCode1
BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image SegmentationCode1
Enhancing Neural Architecture Search with Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT DevicesCode1
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage ModelsCode1
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture SearchCode1
Evolutionary Neural Architecture Search for Transformer in Knowledge TracingCode1
CATE: Computation-aware Neural Architecture Encoding with TransformersCode1
AOWS: Adaptive and optimal network width search with latency constraintsCode1
Evolutionary Neural Cascade Search across SupernetworksCode1
Blockwisely Supervised Neural Architecture Search with Knowledge DistillationCode1
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight TransferCode1
AdvRush: Searching for Adversarially Robust Neural ArchitecturesCode1
BN-NAS: Neural Architecture Search with Batch NormalizationCode1
BM-NAS: Bilevel Multimodal Neural Architecture SearchCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
Few-shot Neural Architecture SearchCode1
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed SpacesCode1
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture SearchCode1
Designing the Topology of Graph Neural Networks: A Novel Feature Fusion PerspectiveCode1
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture SearchCode1
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network QuantizationCode1
FreeREA: Training-Free Evolution-based Architecture SearchCode1
Adversarial Branch Architecture Search for Unsupervised Domain AdaptationCode1
AutoSpeech: Neural Architecture Search for Speaker RecognitionCode1
Hierarchical quantum circuit representations for neural architecture searchCode1
GeNAS: Neural Architecture Search with Better GeneralizationCode1
Can GPT-4 Perform Neural Architecture Search?Code1
Generic Neural Architecture Search via RegressionCode1
Canvas: End-to-End Kernel Architecture Search in Neural NetworksCode1
GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and AttentionCode1
AFter: Attention-based Fusion Router for RGBT TrackingCode1
Bayesian Model Selection, the Marginal Likelihood, and GeneralizationCode1
Bayesian Neural Architecture Search using A Training-Free Performance MetricCode1
Are Labels Necessary for Neural Architecture Search?Code1
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture SearchCode1
β-DARTS: Beta-Decay Regularization for Differentiable Architecture SearchCode1
b-DARTS: Beta-Decay Regularization for Differentiable Architecture SearchCode1
β-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture SearchCode1
Hardware-adaptive Efficient Latency Prediction for NAS via Meta-LearningCode1
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-IdentificationCode1
ColdNAS: Search to Modulate for User Cold-Start RecommendationCode1
HAT: Hardware-Aware Transformers for Efficient Natural Language ProcessingCode1
Block-Wisely Supervised Neural Architecture Search With Knowledge DistillationCode1
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture SearchCode1
Show:102550
← PrevPage 6 of 39Next →

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