neural-architecture-search

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

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)

FedML - The Research and Production Integrated 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

An autoML framework & toolkit for machine learning on graphs.

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

This is a list of interesting papers and projects about TinyML.