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.
Last updated: 6 days agoCode for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
Last updated: 6 days agoA Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
Last updated: 6 days agoPytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs
Last updated: 6 days agoEfficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
Last updated: 6 days agoEfficient computing methods developed by Huawei Noah's Ark Lab
Last updated: 6 days agoThis is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
Last updated: 6 days agoCode for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (...
Last updated: 6 days agoxingtian is a componentized library for the development and verification of reinforcement learning algorithms
Last updated: 6 days agoBinary neural networks developed by Huawei Noah's Ark Lab
Last updated: 6 days agoCode for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
Last updated: 6 days ago