A research library for pytorch-based neural network pruning, compression, and more.
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Updated
Nov 28, 2022 - Shell
A research library for pytorch-based neural network pruning, compression, and more.
[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)
Keras model convolutional filter pruning package
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.
GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning
Knowledge distillation from Ensembles of Iterative pruning (BMVC 2020)
[NeurIPS'21 Spotlight] Aligned Structured Sparsity Learning for Efficient Image Super-Resolution (PyTorch)
Code for CHIP: CHannel Independence-based Pruning for Compact Neural Networks (NeruIPS 2021).
[NIPS 2016] Learning Structured Sparsity in Deep Neural Networks
Official Pytorch implementation of "Filter Pruning by Image Channel Reduction in Pre-Trained Convolutional Neural Networks".
Official repository for the research article "Pruning vs XNOR-Net: A ComprehensiveStudy on Deep Learning for AudioClassification in Microcontrollers"
💍 Efficient tensor decomposition-based 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.
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。
An easy way to conduct filter-pruning for Convolutional layers and fully connected layers
Filter pruning techniques of convolutional neural networks implemented with the Darknet framework.
Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning
In the human synaptic system, there are two important channels known as excitatory and inhibitory neurotransmitters that transmit a signal from a neuron to a cell. Adopting the neuroscientific perspective, we propose a synapse-inspired filter pruning method.
Constraint-Aware Importance Estimation for Global Filter Pruning under Multiple Resource Constraints (CVPRW2020)
code for your paper "Discrete cosine transform for filter pruning"
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