Noah Research
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
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).
Pytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 9分钟前Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
最近更新: 9分钟前A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
最近更新: 9分钟前Pytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs
最近更新: 9分钟前Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 34分钟前This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
最近更新: 34分钟前Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
最近更新: 34分钟前xingtian is a componentized library for the development and verification of reinforcement learning algorithms
最近更新: 34分钟前Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
最近更新: 34分钟前Bolt is a deep learning library with high performance and heterogeneous flexibility.
最近更新: 36分钟前Pytorch code for paper: Learning Versatile Filters for Efficient Convolutional Neural Networks (NeurIPS 2018)
最近更新: 36分钟前