There are 73 repositories under neural-architecture-search topic.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
AutoML library for deep learning
AutoGluon: AutoML for Image, Text, and Tabular Data
Differentiable architecture search for convolutional and recurrent networks
A curated list of automated machine learning papers, articles, tutorials, slides and projects
Fast and flexible AutoML with learning guarantees.
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
Federated Learning Library: https://fedml.ai
Automated deep learning algorithms implemented in PyTorch.
A curated list of awesome architecture search resources
Fast & Simple Resource-Constrained Learning of Deep Network Structure
Genetic neural architecture search with Keras
PaddleSlim is an open-source library for deep model compression and architecture search.
Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019
A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"
a distributed Hyperband implementation on Steroids
[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
Basic implementation of [Neural Architecture Search with Reinforcement Learning](https://arxiv.org/abs/1611.01578).
real-time network architecture for mobile devices and semantic segmentation
Archai accelerates Neural Architecture Search (NAS) through fast, reproducible and modular research.
Awesome Neural Architecture Search Papers
This is a list of interesting papers and projects about TinyML.
PyTorch implementation of PNASNet-5 on ImageNet
Neural Architecture Search Powered by Swarm Intelligence 🐜
Pytorch Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"
Naszilla is a Python library for neural architecture search (NAS)
NASLib is a Neural Architecture Search (NAS) library for facilitating NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces and optimizers.
[ICLR 2020]: 'AtomNAS: Fine-Grained End-to-End Neural Architecture Search'
NSGA-Net, a Neural Architecture Search Algorithm
(CVPR 2020) Block-wisely Supervised Neural Architecture Search with Knowledge Distillation
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
aw_nas: A Modularized and Extensible NAS Framework