84 Open source projects that are alternatives of or similar to Enas Pytorch

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

real-time network architecture for mobile devices and semantic segmentation

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

Genetic neural architecture search with Keras

PyTorch-style and human-readable RegNet with a spectrum of pre-trained models

Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search

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

SGAS: Sequential Greedy Architecture Search (CVPR'2020) https://www.deepgcns.org/auto/sgas

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

[ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang

Minimal Tensorflow implementation of the paper "Neural Architecture Search With Reinforcement Learning" presented at ICLR 2017

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

AutoML frAmework for Neural Networks

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.

DeepArchitect: Automatically Designing and Training Deep Architectures

a distributed Hyperband implementation on Steroids

This directory contains code necessary to run the GraphNAS algorithm.

Fast and flexible AutoML with learning guarantees.

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

AutoGluon: AutoML for Text, Image, and Tabular Data

Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.

Neural Architecture Search Powered by Swarm Intelligence 🐜

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

The official repo for CVPR2021——ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search.

A curated list of awesome architecture search resources

Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search https://arxiv.org/abs/1807.06906

Implement Differentiable Architecture Search (DARTS) for RNN with fastai

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Block-wisely Supervised Neural Architecture Search with Knowledge Distillation (CVPR 2020)

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

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

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

Naszilla is a Python library for neural architecture search (NAS)

Federated Learning Library: https://fedml.ai

A general, modular, and programmable architecture search framework

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

Bridging the gap Between Stability and Scalability in Neural Architecture Search

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

TensorFlow implementation of PNASNet-5 on ImageNet

Differentiable architecture search for convolutional and recurrent networks

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

PyTorch implementation of PNASNet-5 on ImageNet

[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

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

Single Path One-Shot NAS MXNet implementation with full training and searching pipeline. Support both Block and Channel Selection. Searched models better than the original paper are provided.

Reproducible Rapid Research for Neural Architecture Search (NAS)

Automated deep learning algorithms implemented in PyTorch.

NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

NSGA-Net, a Neural Architecture Search Algorithm

Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding. NeurIPS 2020.

[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning

Encodings for neural architecture search

Code for Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells, CVPR '19

[ECCV2020] NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search

Awesome Neural Architecture Search Papers

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

aw_nas: A Modularized and Extensible NAS Framework

"NAS evaluation is frustratingly hard", ICLR2020

AutoML library for deep learning