Alternatives and similar repositories for EPE-NAS

Users that are interested in EPE-NAS are comparing it to the libraries listed below

• VITA-Group / WeakNAS
  [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…
  ☆27Updated 2 years ago
• MAC-AutoML / OMPQ
  ☆25Updated 3 years ago
• yawen-d / TransNASBench
  This repository contains the publishable code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizability of …
  ☆23Updated 2 years ago
• lliai / EMQ-series
  [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
  ☆26Updated last year
• pprp / CVPR2022-NAS-competition-Track1-3th-solution
  Implementation of PGONAS for CVPR22W and RD-NAS for ICASSP23
  ☆22Updated 2 years ago
• orashi / NSE_NAS
  Official PyTorch implementation of "Evolving Search Space for Neural Architecture Search"
  ☆12Updated 4 years ago
• zzzxxxttt / pytorch_simple_DARTS
  A simple pytorch implementation of Differentiable Architecture Search (DARTS)
  ☆19Updated 6 years ago
• A-suozhang / Papers-of-NAS
  Personal Digest of NAS (Under Construction 🛠)
  ☆25Updated 4 years ago
• haolibai / APS-channel-search
  Revisiting Parameter Sharing for Automatic Neural Channel Number Search, NeurIPS 2020
  ☆21Updated 4 years ago
• VITA-Group / TEGNAS
  "Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics" by Wuyang Chen, Xinyu Gong, Yu…
  ☆27Updated 2 years ago
• junjieliu2910 / DynamicSparseTraining
  [ICLR-2020] Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers.
  ☆31Updated 5 years ago
• ArkadiyD / MacroNASBenchmark
  Benchmarks for Macro Neural Architecture Search; used and described in the paper "Local Search is a Remarkably Strong Baseline for Neural…
  ☆12Updated last year
• yukang2017 / NAS-quantization
  The code for Joint Neural Architecture Search and Quantization
  ☆13Updated 6 years ago
• VITA-Group / SFW-Once-for-All-Pruning
  [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…
  ☆32Updated 3 years ago
• xiangning-chen / DrNAS
  Code for our ICLR'2021 paper "DrNAS: Dirichlet Neural Architecture Search"
  ☆43Updated 4 years ago
• automl / DE-NAS
  ☆20Updated 4 years ago
• aaronserianni / training-free-nas
  [ACL'22] Training-free Neural Architecture Search for RNNs and Transformers
  ☆14Updated last year
• SLDGroup / ZiCo
  ☆26Updated 2 years ago
• NivNayman / XNAS
  ☆18Updated 5 years ago
• yaozhewei / HAP
  ☆43Updated last year
• facebookresearch / NASViT
  code for NASViT
  ☆66Updated 3 years ago
• megvii-model / RLNAS
  ☆20Updated 2 years ago
• liuzechun / AdamBNN
  How Do Adam and Training Strategies Help BNNs Optimization? In ICML 2021.
  ☆60Updated 4 years ago
• nabk89 / NAS-with-Proxy-data
  Official code of "NAS acceleration via proxy data", IJCAI21
  ☆10Updated 3 years ago
• IST-DASLab / spdy
  Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"
  ☆20Updated 2 years ago
• lushleaf / Network-Pruning-Greedy-Forward-Selection
  Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
  ☆21Updated 4 years ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆31Updated 2 years ago
• leeyeehoo / GenNAS
  Generic Neural Architecture Search via Regression (NeurIPS'21 Spotlight)
  ☆36Updated 3 years ago
• HayeonLee / HELP
  Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight…
  ☆63Updated last year
• AIoT-MLSys-Lab / CATE
  [ICML 2021 Oral] "CATE: Computation-aware Neural Architecture Encoding with Transformers" by Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
  ☆19Updated 4 years ago