Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
Noah Research
A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
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).
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 12天前A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
最近更新: 12天前Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
最近更新: 12天前Pytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs
最近更新: 12天前Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 12天前This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
最近更新: 12天前Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
最近更新: 12天前xingtian is a componentized library for the development and verification of reinforcement learning algorithms
最近更新: 12天前