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178 search results found

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

Autokeras ⭐ 9,067

AutoML library for deep learning

Awesome Automl Papers ⭐ 3,607

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

Adanet ⭐ 3,309

Fast and flexible AutoML with learning guarantees.

Darts ⭐ 2,775

Differentiable architecture search for convolutional and recurrent networks

Enas Pytorch ⭐ 2,242

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

Awesome Autodl ⭐ 2,207

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)

Autodl Projects ⭐ 1,546

Automated deep learning algorithms implemented in PyTorch.

Awesome Federated Learning ⭐ 1,481

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

Autogl ⭐ 1,035

An autoML framework & toolkit for machine learning on graphs.

Awesome Architecture Search ⭐ 1,011

A curated list of awesome architecture search resources

Morph Net ⭐ 1,010

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Genetic neural architecture search with Keras

Randwirenn ⭐ 663

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

Awesome Automl And Lightweight Models ⭐ 647

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 ⭐ 623

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

Tinyengine ⭐ 614

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

Tinyml Papers And Projects ⭐ 566

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

Hpbandster ⭐ 551

a distributed Hyperband implementation on Steroids

Fasterseg ⭐ 523

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

Hyperactive ⭐ 475

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Autogan ⭐ 460

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

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.

Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.

Real Time Network ⭐ 374

real-time network architecture for mobile devices and semantic segmentation

Syne Tune ⭐ 342

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization

Neural Architecture Search ⭐ 312

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

Pnasnet.pytorch ⭐ 299

PyTorch implementation of PNASNet-5 on ImageNet

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning

Naszilla ⭐ 269

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

Nn Meter ⭐ 265

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Randwirenn ⭐ 259

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

Awesome Nas Papers ⭐ 258

Awesome Neural Architecture Search Papers

Hypernets ⭐ 256

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Deephyper ⭐ 253

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

Deepswarm ⭐ 245

Neural Architecture Search Powered by Swarm Intelligence 🐜

aw_nas: A Modularized and Extensible NAS Framework

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

Hyperts ⭐ 225

A Full-Pipeline Automated Time Series (AutoTS) Analysis Toolkit.

[ACL-IJCNLP 2021] Automated Concatenation of Embeddings for Structured Prediction

Awesome Transformer Search ⭐ 206

A curated list of awesome resources combining Transformers with Neural Architecture Search

Autospeech ⭐ 204

[InterSpeech 2020] "AutoSpeech: Neural Architecture Search for Speaker Recognition" by Shaojin Ding*, Tianlong Chen*, Xinyu Gong, Weiwei Zha, Zhangyang Wang

Lycoris ⭐ 188

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

Single Path One Shot Nas Mxnet ⭐ 148

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.

Atomnas ⭐ 148

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

Nas Benchmark ⭐ 148

[ICLR 2020] NAS evaluation is frustratingly hard

Deep_architect_legacy ⭐ 146

DeepArchitect: Automatically Designing and Training Deep Architectures

Scarlet Nas ⭐ 141

Bridging the gap Between Stability and Scalability in Neural Architecture Search

Graphnas ⭐ 135

This directory contains code necessary to run the GraphNAS algorithm.

Torchprune ⭐ 130

A research library for pytorch-based neural network pruning, compression, and more.

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

Evonorm ⭐ 119

Unofficial PyTorch Implementation of EvoNorm

Nsga Net ⭐ 114

NSGA-Net, a Neural Architecture Search Algorithm

Petridishnn ⭐ 110

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

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Nas Segm Pytorch ⭐ 108

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

A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)

Bossnas ⭐ 104

(ICCV 2021) BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search

[ICML2020] "AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks" by Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang

Pnasnet.tf ⭐ 101

TensorFlow implementation of PNASNet-5 on ImageNet

Deep_architect ⭐ 98

A general, modular, and programmable architecture search framework

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

Receptive_field_analysis_toolbox ⭐ 91

A toolbox for receptive field analysis and visualizing neural network architectures

Nsganetv2 ⭐ 89

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

H. Zhang, Q. Yao, M. Yang, Y. Xu, X. Bai. AutoSTR: Efficient Backbone Search for Scene Text Recognition. European Conference on Computer Vision (ECCV). 2020.

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

Awesome Auto Graph Learning ⭐ 77

A paper collection about automated graph learning

Enas Keras ⭐ 76

Keras implementation of Efficient Neural Architecture Search

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

Open Source Neural Architecture Search Toolbox for Device-aware Image Dense Prediction & Official implementation of ICCV2021 "iNAS: Integral NAS for Device-Aware Salient Object Detection"

Instanas ⭐ 72

⚡️ [AAAI'20][ICML'19 AutoML] InstaNAS: Instance-aware Neural Architecture Search

Evoxbench ⭐ 63

Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.

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

Naspapers ⭐ 59

Paper lists of neural architecture search (NAS)

Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

Litmatter ⭐ 55

Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.

Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)

TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search (ECCV2020)

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

PyTorch implementation of Pose Neural Fabrics Search (PNFS)--Part-specific neural architecture search for human pose estimation.

Costar_plan ⭐ 49

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

Arch2vec ⭐ 47

[NeurIPS 2020] "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?" by Shen Yan, Yu Zheng, Wei Ao, Xiao Zeng, Mi Zhang

Efficientnas ⭐ 46

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

Nasbench Pytorch ⭐ 43

A PyTorch implementation of NASBench

Pocketnet ⭐ 42

Official repository for PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation

Lighthubert ⭐ 42

LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT

Exploring Relational Context for Multi-Task Dense Prediction [ICCV 2021]

This is a collection of our research on efficient AI, covering hardware-aware NAS and model compression.

Pytorch Cifar10 ⭐ 39

The state-of-the-art algorithms on CIFAR-10 dataset in PyTorch

Neural Architecture Search With Rl ⭐ 37

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

Unified Architecture Search with Convolution, Transformer, and MLP (ECCV 2022)

Minimal Nas ⭐ 36

Minimal implementation of a Neural Architecture Search system.

Sandwich Batch Normalization ⭐ 35

[WACV 2022] "Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity" by Xinyu Gong, Wuyang Chen, Tianlong Chen and Zhangyang Wang

reimplementation of "Learning Transferable Architectures for Scalable Image Recognition" using mnist dataset, include controller

Interstellar ⭐ 33

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

[CVPR 2021] Contrastive Neural Architecture Search with Neural Architecture Comparators

Efficient Bert ⭐ 31

This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".

Hierarqcal ⭐ 31

Generate hierarchical quantum circuits for Neural Architecture Search.

Intel® End-to-End AI Optimization Kit

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