huangleiBuaa
Associate professor in BeiHang University, research interest: deep learning, semi-supervised learning, active learning and their application to visual dada
Beihang University, Associate ProfessorBeijing, China
Pinned Repositories
CenteredWN
This project is the Torch implementation of our ICCV 2017 paper: Centered Weight Normalization in Accelerating Training of Deep Neural Networks
IterNorm
This project is the Torch implementation of our accepted CVPR 2019 paper, Iterative Normalization: Beyond Standardization towards Efficient Whitening
IterNorm-pytorch
This is the pytorch re-implementation of the IterNorm
LRCount-CNN
This code is for our ICML 2020 paper "On the Number of Linear Regions of Convolutional Neural Networks."
NormalizationSurvey
This repo is for our paper: Normalization Techniques in Training DNNs: Methodology, Analysis and Application
ONI
PyTorch and Torch implementation for our accepted CVPR 2020 paper (Oral): Controllable Orthogonalization in Training DNNs
OthogonalWN
This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonality constraints over Steifel manifold in deep neural networks (arXiv:1709.06079 )
StochasticityBW
PyTorch and Tensorflow implementation for our accepted CVPR 2020 paper (Oral): An Investigation into the Stochasticity of Batch Whitening
XBNBlock
This project is the PyTorch implementation of our CVPR 2022 paper:
DecorrelatedBN
Code for Decorrelated Batch Normalization
huangleiBuaa's Repositories
huangleiBuaa/NormalizationSurvey
This repo is for our paper: Normalization Techniques in Training DNNs: Methodology, Analysis and Application
huangleiBuaa/OthogonalWN
This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonality constraints over Steifel manifold in deep neural networks (arXiv:1709.06079 )
huangleiBuaa/IterNorm-pytorch
This is the pytorch re-implementation of the IterNorm
huangleiBuaa/XBNBlock
This project is the PyTorch implementation of our CVPR 2022 paper:
huangleiBuaa/IterNorm
This project is the Torch implementation of our accepted CVPR 2019 paper, Iterative Normalization: Beyond Standardization towards Efficient Whitening
huangleiBuaa/ONI
PyTorch and Torch implementation for our accepted CVPR 2020 paper (Oral): Controllable Orthogonalization in Training DNNs
huangleiBuaa/CenteredWN
This project is the Torch implementation of our ICCV 2017 paper: Centered Weight Normalization in Accelerating Training of Deep Neural Networks
huangleiBuaa/LRCount-CNN
This code is for our ICML 2020 paper "On the Number of Linear Regions of Convolutional Neural Networks."
huangleiBuaa/StochasticityBW
PyTorch and Tensorflow implementation for our accepted CVPR 2020 paper (Oral): An Investigation into the Stochasticity of Batch Whitening
huangleiBuaa/GroupWhitening
This project is the PyTorch implementation of our accepted CVPR 2021 paper, Group Whitening: Balancing Learning Efficiency and Representational Capacity
huangleiBuaa/Active-GBSSL
This is a project of my paper related to active learning and graph based semi-supervised learning, which is published on ICME 2014. The project is written by matlab
huangleiBuaa/NormProjection
This project is the Torch implementation of the paper: Projection Based Weight Normalization for Deep Neural Networks (arXiv:1710.02338)
huangleiBuaa/LayerwiseCA
This project is for the paper: Exploring learning dynamics of DNNs via layerwise conditioning analysis
huangleiBuaa/Ladder_deepSSL_NP
The reimplementation of Ladder networks with projection based weight normalization. We achieved test errors as 2.52%, 1.06%, and 0.91% on Permunate invariant MNIST dataset with 20, 50, and 100 labeled samples respectively, which is the state-of-the-art results.
huangleiBuaa/huangleiBuaa.github.io
huangleiBuaa/chauff.github.io
Website & blog
huangleiBuaa/decorrelated_bn
An implementation of DecorrelatedBN by tensorflow
huangleiBuaa/maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.