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.

[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

Awesome Neural Architecture Search Papers

AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch

A PyTorch implementation of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.

DeepArchitect: Automatically Designing and Training Deep Architectures

A general, modular, and programmable architecture search framework

Repository to track the progress in model compression and acceleration

A Tensorflow Keras implementation (Graph and eager execution) of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.

Integrating learning and task planning for robots with Keras, including simulation, real robot, and multiple dataset support.

A Fast DNN Accelerator Design Space Exploration Framework.

Evolve Flux networks from scratch!

Your local Flux surgeon

This github repository contains the official code for the paper, "Evolving Robust Neural Architectures to Defend from Adversarial Attacks"

Relentless mutation!!

A neural architecture optimizer, targeted at model-size w.r.t. accuracy

sharpDARTS: Faster and More Accurate Differentiable Architecture Search

Implementation of MetaQNN (https://arxiv.org/abs/1611.02167, https://github.com/bowenbaker/metaqnn.git) with Additions and Modifications in PyTorch for Image Classification

Implementation of Autoslim using Tensorflow2

Distributed Network Architecture Search