A research library for pytorch-based neural network pruning, compression, and more.

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning

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

[NeurIPS'21 Spotlight] Aligned Structured Sparsity Learning for Efficient Image Super-Resolution (PyTorch)

Keras model convolutional filter pruning package

Code for CHIP: CHannel Independence-based Pruning for Compact Neural Networks (NeruIPS 2021).

Knowledge distillation from Ensembles of Iterative pruning (BMVC 2020)

[NIPS 2016] Learning Structured Sparsity in Deep Neural Networks

Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning

Cheng-Hao Tu, Jia-Hong Lee, Yi-Ming Chan and Chu-Song Chen, "Pruning Depthwise Separable Convolutions for MobileNet Compression," International Joint Conference on Neural Networks, IJCNN 2020, July 2020.

💍 Efficient tensor decomposition-based filter pruning

Official repository for the research article "Pruning vs XNOR-Net: A ComprehensiveStudy on Deep Learning for AudioClassification in Microcontrollers"

Filter pruning techniques of convolutional neural networks implemented with the Darknet framework.

🌠 Enhanced Network Compression Through Tensor Decompositions and Pruning

对人像抠图模型MODNet进行滤波器级别的剪枝，结合自适应与固定比例策略。

🧠 Singular values-driven automated filter pruning

code for your paper "Discrete cosine transform for filter pruning"

Official Pytorch implementation of "Filter Pruning by Image Channel Reduction in Pre-Trained Convolutional Neural Networks".

An easy way to conduct filter-pruning for Convolutional layers and fully connected layers