MarttiWu

MarttiWu's Stars

• cwtsaiai/metaheuristics_2023

  Language:C++103

• cwtsaiai/TNASSE

  Language:Python8

• D-X-Y/NATS-Bench

  TPAMI 2021: NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

  Language:Python17320

• google-research/nasbench

  NASBench: A Neural Architecture Search Dataset and Benchmark

  Language:Python681129

• D-X-Y/NAS-Bench-201

  NAS-Bench-201 API and Instruction

  Language:Python624117

• automl/nasbench301

  Language:Python7322

• automl/nasbench-1shot1

  Language:Python6714

• fmsnew/nas-bench-nlp-release

  Language:Jupyter Notebook258

• rtu715/NAS-Bench-360

  Introducing diverse tasks for NAS

  Language:Python473

• VascoLopes/EPE-NAS

  Language:Python255

• microsoft/archai

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

  Language:Python46491

• NiccoloCavagnero/FreeREA

  Official implementation of "FreeREA: Training-Free Evolution-based Architecture Search"

  Language:Python93

• VITA-Group/AsViT

  [ICLR 2022] "As-ViT: Auto-scaling Vision Transformers without Training" by Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou

  Language:Python764

• cmu-catalyst/GradSign

  Code for paper GradSign: Model Performance Inference with Theoretical Insights

  Language:Python7

• YiteWang/MetaNTK-NAS

  Language:Python122

• nassimmokhtari/Improved-FireFly-Algorithm

  This project represents the implementation of the training-free model evaluation based on the Intra-Cluster Distance, and the improved firefly algorithm (IFA) used in our paper "Improving Neural Architecture Search by Mixing a FireFly algorithm with a Training Free Evaluation" published in IJCNN 2022

  Language:Python71

• alibaba/lightweight-neural-architecture-search

  This is a collection of our zero-cost NAS and efficient vision applications.

  Language:Python37149

• RobGeada/SpiderNet-NTKLRC

  Train-free SpiderNet

  Language:Jupyter Notebook41

• acamero/dlopt

  Deep learning architecture optimization

  Language:Python125

• Jingjing-NLP/KNAS

  Codes for paper "KNAS: Green Neural Architecture Search"

  Language:Python9215

• VITA-Group/TENAS

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

  Language:Python16431

• BayesWatch/nas-without-training

  Code for Neural Architecture Search without Training (ICML 2021)

  Language:Python45562

• TuDo1403/TF-MOENAS

  [ICONIP 2021] "Training-Free Multi-Objective Evolutionary Neural Architecture Search via Neural Tangent Kernel and Number of Linear Regions" by Tu Do, Ngoc Hoang Luong

  Language:Python6

• VITA-Group/TEGNAS

  "Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics" by Wuyang Chen, Xinyu Gong, Yunchao Wei, Humphrey Shi, Zhicheng Yan, Yi Yang, and Zhangyang Wang

  Language:Python254

• idstcv/ZenNAS

  Language:Python21935

• SamsungLabs/zero-cost-nas

  Zero-Cost Proxies for Lightweight NAS

  Language:Jupyter Notebook14020

• google-research/google-research

  Google Research

  Language:Jupyter Notebook34k7.8k

• microsoft/Bringing-Old-Photos-Back-to-Life

  Bringing Old Photo Back to Life (CVPR 2020 oral)

  Language:Python15k2k

• D-X-Y/Awesome-AutoDL

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

  Language:Python2.2k314

• walkerning/aw_nas

  aw_nas: A Modularized and Extensible NAS Framework

  Language:Python24631