model compression based on pytorch (1、quantization: 16/8/4/2 bits(dorefa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、ternary/binary value(twn/bnn/xnor-net)；2、 pruning: normal、regular and group convolutional channel pruning；3、 group convolution structure；4、batch-normalization folding for quantization)

ShuffleNet Implementation in TensorFlow

E(2)-Equivariant CNNs Library for Pytorch

PyTorch implementation of Dynamic Grouping Convolution and Groupable ConvNet with pre-trained G-ResNeXt models

Code repository of the paper "Wavelet Networks: Scale Equivariant Learning From Raw Waveforms" https://arxiv.org/abs/2006.05259

Code repository for the paper "Attentive Group Equivariant Convolutional Neural Networks" published at ICML 2020. https://arxiv.org/abs/2002.03830

Implementation of "Fully Learnable Group Convolution for Acceleration of Deep Neural Networks", CVPR'19

Code repository for paper "Efficient Structured Pruning and Architecture Searching for Group Convolution" https://arxiv.org/abs/1811.09341

PyTorch Implementation of Mobilenet Variants including support for residual connections, group convolutions and squeeze-excite blocks