csyhhu / Awesome-Deep-Neural-Network-Compression
Summary, Code for Deep Neural Network Quantization
☆548Updated 6 months ago
Alternatives and similar repositories for Awesome-Deep-Neural-Network-Compression:
Users that are interested in Awesome-Deep-Neural-Network-Compression are comparing it to the libraries listed below
- Collection of recent methods on (deep) neural network compression and acceleration.☆945Updated 3 weeks ago
- Papers for deep neural network compression and acceleration☆397Updated 3 years ago
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆440Updated last year
- PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by …☆419Updated 5 years ago
- ☆668Updated 3 years ago
- PyTorch implementation for the APoT quantization (ICLR 2020)☆271Updated 4 months ago
- PyTorch library to facilitate development and standardized evaluation of neural network pruning methods.☆429Updated last year
- [CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision☆382Updated 4 years ago
- [CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework☆277Updated last year
- Awesome machine learning model compression research papers, quantization, tools, and learning material.☆510Updated 7 months ago
- Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)☆1,515Updated 4 years ago
- PyTorch implementation of Data Free Quantization Through Weight Equalization and Bias Correction.☆262Updated last year
- Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.☆431Updated last year
- Quantization of Convolutional Neural networks.☆244Updated 8 months ago
- papers about model compression☆166Updated 2 years ago
- Pruning Neural Networks with Taylor criterion in Pytorch☆317Updated 5 years ago
- Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626☆177Updated 2 years ago
- Model Quantization Benchmark☆799Updated this week
- Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks☆381Updated 5 years ago
- MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning. In ICCV 2019.☆354Updated 4 years ago
- Pytorch implementation of BRECQ, ICLR 2021☆272Updated 3 years ago
- Repository to track the progress in model compression and acceleration☆105Updated 3 years ago
- Implements quantized distillation. Code for our paper "Model compression via distillation and quantization"☆332Updated 9 months ago
- Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.☆568Updated 5 years ago
- Low Precision Arithmetic Simulation in PyTorch☆275Updated 11 months ago
- A simple network quantization demo using pytorch from scratch.☆527Updated last year
- A curated list of neural network pruning resources.☆2,437Updated last year
- On-the-fly Structured Pruning for PyTorch models. This library implements several attributions metrics and structured pruning utils for n…☆164Updated 4 years ago
- A general and accurate MACs / FLOPs profiler for PyTorch models☆604Updated 11 months ago
- Network Slimming (Pytorch) (ICCV 2017)☆915Updated 4 years ago