Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
Noah Research
Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (NeurIPS 2020) and “Manifold Regularized Dynamic Network Pruning” (CVPR 2021).
stream Machine Learning in C++
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 7小时前Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
最近更新: 7小时前A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
最近更新: 7小时前Pytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs
最近更新: 7小时前Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 8小时前This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
最近更新: 8小时前Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
最近更新: 8小时前xingtian is a componentized library for the development and verification of reinforcement learning algorithms
最近更新: 8小时前