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Neural Architecture Search

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하위 태스크: 1
평가표: 26
보존된 평가 기록: 424

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/saintslab/ec-nas-bench

공식 코드

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search

https://github.com/sanaelotfi/bayesian_model_comparison

공식 코드

Bayesian Model Selection, the Marginal Likelihood, and Generalization

https://github.com/sashwatanagolum/elivagar

공식 코드

Élivágar: Efficient Quantum Circuit Search for Classification

https://github.com/sbb-gh/prosub

공식 코드

Progressive Subsampling for Oversampled Data -- Application to Quantitative MRI

https://github.com/sdl-asu/acla

공식 코드

Adaptive Cross-Layer Attention for Image Restoration

https://github.com/sense-x/uninet

공식 코드

UniNet: Unified Architecture Search with Convolution, Transformer, and MLP

https://github.com/sg-nm/cgp-cnn

공식 코드

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures

https://github.com/sh-src/automf

공식 코드

Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions

https://github.com/shaanpakala/stc_automl

공식 코드

Automating Data Science Pipelines with Tensor Completion

https://github.com/shangzongjiang/SNAS4MTF

공식 코드

Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

https://github.com/shashankkotyan/RobustArchitectureSearch

공식 코드

Evolving Robust Neural Architectures to Defend from Adversarial Attacks

https://github.com/shipxu123/NAC

공식 코드

Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

https://github.com/shirakawas/ASNG-NAS

공식 코드

Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search

https://github.com/shuyao95/HNAS

공식 코드

Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search

https://github.com/shuyao95/Understanding-NAS

공식 코드

Understanding Architectures Learnt by Cell-based Neural Architecture Search

https://github.com/sjiang87/deephyper

공식 코드

Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search

https://github.com/sjunhongshen/dash

공식 코드

Efficient Architecture Search for Diverse Tasks

https://github.com/skhu101/GM-NAS

공식 코드

Generalizing Few-Shot NAS with Gradient Matching

https://github.com/skhu101/tdnn-f_nas

공식 코드

Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks

https://github.com/sldgroup/survey-zero-shot-nas

공식 코드

Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities

https://github.com/slds-lmu/qdo_nas

공식 코드

Tackling Neural Architecture Search With Quality Diversity Optimization

https://github.com/snu-adsl/bbea

공식 코드

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search

https://github.com/sprocketlab/sparse_matrix_fine_tuning

공식 코드

MoRe Fine-Tuning with 10x Fewer Parameters

https://github.com/sserranw/abg-nas

공식 코드

ABG-NAS: Adaptive Bayesian Genetic Neural Architecture Search for Graph Representation Learning

https://github.com/statistical-deep-learning/dcs-attention

공식 코드

Differentiable Channel Selection in Self-Attention For Person Re-Identification

https://github.com/stepbuystep/lightnas

공식 코드

You Only Search Once: On Lightweight Differentiable Architecture Search for Resource-Constrained Embedded Platforms

https://github.com/striderdu/spa

공식 코드

Search to Pass Messages for Temporal Knowledge Graph Completion

https://github.com/sunsmarterjie/DAAS

공식 코드

Discretization-Aware Architecture Search

https://github.com/sunsmarterjie/SDL-Skeleton

공식 코드

Adaptive Linear Span Network for Object Skeleton Detection

https://github.com/susan0199/stacnas

공식 코드

Hierarchical Neural Architecture Search via Operator Clustering

https://github.com/talcs/naap-440

공식 코드

NAAP-440 Dataset and Baseline for Neural Architecture Accuracy Prediction

https://github.com/taloncb/manas

공식 코드

Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS)

https://github.com/tanglang96/DDPNAS

공식 코드

DDPNAS: Efficient Neural Architecture Search via Dynamic Distribution Pruning

https://github.com/tanglang96/MDENAS

공식 코드

Multinomial Distribution Learning for Effective Neural Architecture Search

https://github.com/taoyang1122/revisit_trainingfree_nas

공식 코드

Revisiting Training-free NAS Metrics: An Efficient Training-based Method

https://github.com/tdchaitanya/nas-robustness

공식 코드

On Adversarial Robustness: A Neural Architecture Search perspective

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