AutoML library for deep learning

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Fast and flexible AutoML with learning guarantees.

Differentiable architecture search for convolutional and recurrent networks

A curated list of automated machine learning papers, articles, tutorials, slides and projects

PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.

A curated list of awesome architecture search resources

Automated deep learning algorithms implemented in PyTorch.

Genetic neural architecture search with Keras

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"

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.

Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019

PaddleSlim is an open-source library for deep model compression and architecture search.

a distributed Hyperband implementation on Steroids

[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang

Basic implementation of [Neural Architecture Search with Reinforcement Learning](https://arxiv.org/abs/1611.01578).

[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang

PyTorch implementation of PNASNet-5 on ImageNet

Pytorch Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"

Neural Architecture Search Powered by Swarm Intelligence 🐜

real-time network architecture for mobile devices and semantic segmentation

A lightweight and easy-to-use deep learning framework with neural architecture search.

Code for ICLR 2020 paper 'AtomNAS: Fine-Grained End-to-End Neural Architecture Search'

DeepArchitect: Automatically Designing and Training Deep Architectures

NSGA-Net, a Neural Architecture Search Algorithm

Bayesian Optimization with Neural Architectures for Neural Architecture Search - https://arxiv.org/abs/1910.11858

Bridging the gap Between Stability and Scalability in Neural Architecture Search

AutoML frAmework for Neural Networks