network-compression

Model Compression Toolkit (MCT) is an open source project for neural network model optimization under efficient, constrained hardware. This project provides researchers, developers, and engineers advanced quantization and compression tools for deploying state-of-the-art neural networks.

machine-learning deep-neural-networks deep-learning neural-network tensorflow optimizer pytorch quantization qat network-quantization network-compression edge-ai ptq

UpdatedFeb 12, 2026
Python

clovaai /overhaul-distillation

Star423

Official PyTorch implementation of "A Comprehensive Overhaul of Feature Distillation" (ICCV 2019)

knowledge-distillation teacher-student knowledge-transfer network-compression iccv2019

UpdatedJun 23, 2020
Python

A-suozhang /awesome-quantization-and-fixed-point-training

Star161

Neural Network Quantization & Low-Bit Fixed Point Training For Hardware-Friendly Algorithm Design

fixed-point quantization network-compression

UpdatedDec 18, 2020

jshilong /FisherPruning

Star161

Group Fisher Pruning for Practical Network Compression(ICML2021)

pruning network-compression

UpdatedMay 24, 2023
Python

uber-research /permute-quantize-finetune

Star145

Using ideas from product quantization for state-of-the-art neural network compression.

deep-learning vector-quantization network-compression

UpdatedAug 14, 2021
Python

bhheo /AB_distillation

Star106

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons (AAAI 2019)

transfer-learning knowledge-distillation knowledge-transfer network-compression teacher-student-learning

UpdatedSep 9, 2019
Python

musco-ai /musco-pytorch

Star72

MUSCO: MUlti-Stage COmpression of neural networks

deep-neural-networks pytorch tensor-decomposition cp-decomposition tucker model-compression network-acceleration model-acceleration truncated-svd network-compression low-rank vbmf

UpdatedFeb 16, 2021
Jupyter Notebook

bhheo /BSS_distillation

Star71

Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)

image-classification knowledge-distillation adversarial-samples adversarial-attacks network-compression teacher-student-learning

UpdatedSep 9, 2019
Python

ofsoundof /group_sparsity

Star64

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.

low-rank-approximation network-compression filter-pruning proximal-gradient-descent group-sparsity

UpdatedJan 17, 2026
Python

ofsoundof /dhp

Star58

This is the official implementation of "DHP: Differentiable Meta Pruning via HyperNetworks".

pruning meta-learning hypernetworks differentiable network-compression

UpdatedJan 17, 2026
Python

vantienpham /CORING

Star33

💍 Efficient tensor decomposition-based filter pruning

tensor-decomposition network-pruning hosvd network-compression tucker-decomposition filter-pruning structured-pruning tinyml

UpdatedJul 23, 2025
Jupyter Notebook

ofsoundof /learning_filter_basis

Star18

Pytorch implemenation of "Learning Filter Basis for Convolutional Neural Network Compression" ICCV2019

image-classification super-resolution low-rank-approximation network-compression

UpdatedJan 17, 2026
Python

Zhengyu-Li /Deep-Network-Compression-based-on-Student-Teacher-Network-

Star14

Deep Neural Network Compression based on Student-Teacher Network

tensorflow densenet deeplearning multi-gpu teacher-student network-compression

UpdatedJul 6, 2023
Python

yukaikw /Machine-Learning

Star12

李宏毅教授 ML 2020 機器學習課程筆記 & 實作

machine-learning deep-learning regression cnn gan classification rnn transfer-learning unsupervised-learning anomaly-detection adversarial-attacks explainable-ai network-compression

UpdatedDec 20, 2021
Python

quic /aimet-pages

Star10

AIMET GitHub pages documentation

open-source machine-learning opensource deep-neural-networks compression deep-learning pruning quantization auto-ml network-quantization network-compression

UpdatedFeb 10, 2026
HTML

cambridge-mlg /arch_uncert

Star9

Code for "Variational Depth Search in ResNets" (https://arxiv.org/abs/2002.02797)

reproducible-research uncertainty mnist expectation-maximization svhn bayesian-inference variational-inference residual-networks bayesian-neural-networks neural-architecture-search bayesian-deep-learning fashion-mnist reproducible-paper resnets network-compression sparse-neural-networks learnt-depth network-depths

UpdatedJun 12, 2020
Jupyter Notebook

malena1906 /Pruning-Weights-with-Biobjective-Optimization-Keras

Star9

Overparameterization and overfitting are common concerns when designing and training deep neural networks. Network pruning is an effective strategy used to reduce or limit the network complexity, but often suffers from time and computational intensive procedures to identify the most important connections and best performing hyperparameters. We s…

machine-learning sparsity ai tensorflow keras python3 image-classification automl l1-regularization network-compression unstructured-weight-pruning multiobjective-learning soft-pruning stochastic-multi-gradient dichotomic-serach dense-layers

UpdatedSep 1, 2020
Python

musco-ai /musco-tf

Star8

MUSCO: Multi-Stage COmpression of neural networks

deep-neural-networks tensorflow tensor-decomposition cp-decomposition tucker low-rank-approximation truncated-svd network-compression vbmf musco cnn-compresion cnn-acceleration

UpdatedJan 7, 2021
Python

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