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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Summary, Code for Deep Neural Network Quantization
| Date | Stars |
|---|---|
| 2026-07-31 | 562 |
| 2026-08-01 | 563 |
| 2026-08-02 | 564 |
| 2026-08-06 | 564 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
[](https://GitHub.com/Naereen/ama)
[](https://awesome.re)
# Awesome Deep Neural Network Compression
Paper collection, Summary, Code for Deep Neural Network Compression, including:
- Quantization,
- Pruning (Unstructure, structure)
- Distillation
and so on.
## Paper:
+ By Topic:
- [Quantization](./Paper/Quantization.md)
- [Pruning](./Paper/Pruning.md)
- [Efficient Model Design](./Paper/Efficient-Model-Design.md)
- [Network Architecture Search (NAS) for Model Compression](./Paper/NAS.md)
- [Compression Meets Robustness (Adversarial)](./Paper/Robust-Compression.md)
- [NLP Compression](./Paper/NLP-Compression.md)
- [Differentiable Compression](./Paper/Differentiable-Compression.md)
- [Large Pretraining Models](Paper/Large-Pretraining-Models/Overall.md): Including language, vision
+ [By Conference](./Paper/PaperByConference.md):
- [2024](./Paper/Conference/2024.md)
- [2023](./Paper/Conference/2023.md)
- [2022](./Paper/Conference/2022.md)
- [2021](./Paper/Conference/2021.md)
- [2020](./Paper/Conference/2020.md)
- [2019](./Paper/Conference/2019.md)
- [2018](./Paper/Conference/2018.md)
+ [Survey](./Paper/survey.md)
+ Related Topic:
- [Optimization](./)
- [Meta Learning](./Paper/Meta-Learning.md)
## Compression System:
* [DeepSpeed](https://github.com/microsoft/DeepSpeed)
* [ColossalAI](https://github.com/hpcaitech/ColossalAI)
* [Distiller](https://nervanasystems.github.io/distiller/)
* [PocketFlow](https://github.com/Tencent/PocketFlow)
## Codes / Tools:
+ [My Implementation](./Codes): My re-implementation of state-of-the-art compression methods.
## Summary:
My summary (slides) for network compression. Some papers are chosen to be represented.
* [Quantization Summary](./Summary/Quantization-Summary.pdf)
* [Pruning Summary](./Summary/Prunning-Summary.pdf)
* Theory: From basic convex optimization to quantizationExcerpt of 2,444 characters
Read on GitHub
46
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c37cd9486252d052, desc:quantization