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: 4天前A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
最近更新: 4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: 4天前Pytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs
最近更新: 4天前Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 4天前Efficient computing methods developed by Huawei Noah's Ark Lab
最近更新: 4天前Pytorch code for paper: Learning Versatile Filters for Efficient Convolutional Neural Networks (NeurIPS 2018)
最近更新: 4天前A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
最近更新: 4天前Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
最近更新: 4天前This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
最近更新: 4天前