Alternatives and similar repositories for nnabla-nas

Users that are interested in nnabla-nas are comparing it to the libraries listed below

• facebookresearch / AlphaNet
  AlphaNet Improved Training of Supernet with Alpha-Divergence
  ☆100Updated 4 years ago
• yaozhewei / HAP
  ☆43Updated last year
• facebookresearch / NASViT
  code for NASViT
  ☆67Updated 3 years ago
• IST-DASLab / spdy
  Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"
  ☆20Updated 2 years ago
• Qualcomm-AI-research / oscillations-qat
  ☆78Updated 3 years ago
• 1adrianb / binary-networks-pytorch
  Binarize convolutional neural networks using pytorch
  ☆149Updated 3 years ago
• MAC-AutoML / OMPQ
  ☆25Updated 4 years ago
• lucaslie / torchprune
  A research library for pytorch-based neural network pruning, compression, and more.
  ☆163Updated 3 years ago
• SLDGroup / ZiCo
  ☆28Updated 2 years ago
• 1hunters / LIMPQ
  Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"
  ☆61Updated 2 years ago
• lliai / EMQ-series
  [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
  ☆28Updated 2 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…
  ☆33Updated 3 years ago
• GATECH-EIC / HW-NAS-Bench
  [ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
  ☆113Updated 2 years ago
• snap-research / F8Net
  [ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization
  ☆93Updated 3 years ago
• facebookresearch / DepthShrinker
  [ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan …
  ☆72Updated 3 years ago
• sony-si / ai-research
  ☆48Updated 5 years ago
• VITA-Group / Random_Pruning
  [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…
  ☆77Updated 2 years ago
• mlzxy / qsparse
  Train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules
  ☆43Updated 3 years ago
• 1adrianb / expert-binary-networks
  Code for High-Capacity Expert Binary Networks (ICLR 2021).
  ☆27Updated 4 years ago
• gilshm / sparq
  Post-training sparsity-aware quantization
  ☆34Updated 2 years ago
• jakc4103 / scale-adjusted-training
  PyTorch implementation of Towards Efficient Training for Neural Network Quantization
  ☆16Updated 5 years ago
• ziplab / SAQ
  This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
  ☆43Updated 4 years ago
• idstcv / ZenNAS
  ☆229Updated 4 years ago
• VascoLopes / EPE-NAS
  ☆26Updated 3 years ago
• Jangho-Kim / PSG-pytorch
  Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)
  ☆25Updated 5 years ago
• eliberis / uNAS
  μNAS is a neural architecture search (NAS) system that designs small-yet-powerful microcontroller-compatible neural networks.
  ☆82Updated 4 years ago
• gatech-sysml / CompOFA
  [ICLR 2021] CompOFA: Compound Once-For-All Networks For Faster Multi-Platform Deployment
  ☆25Updated 2 years ago
• IntelLabs / DyNAS-T
  Dynamic Neural Architecture Search Toolkit
  ☆31Updated last year
• ziplab / EcoFormer
  [NeurIPS 2022 Spotlight] This is the official PyTorch implementation of "EcoFormer: Energy-Saving Attention with Linear Complexity"
  ☆74Updated 3 years ago
• GATECH-EIC / ShiftAddNet
  [NeurIPS 2020] ShiftAddNet: A Hardware-Inspired Deep Network
  ☆74Updated 5 years ago