Duan YuanZheng's repositories
segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
BIfuse_CubeMap
[CVPR2020] BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion
MappedConvolutions
Official PyTorch implementation of Mapped Convolutions
Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
HexRUNet_pytorch
An unofficial PyTorch implementation of ICCV 2019 paper "Orientation-Aware Semantic Segmentation on Icosahedron Spheres"
dl-uncertainty
"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
Deep-Learning-with-TensorFlow-book
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
GraphNeuralNetwork
The learning of the GraphNeuralNetwork
Python
My Python Examples
tensorflow2_tutorials_chinese
tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials
SpherePHD_py
Reproduce SpherePHD with python codes
Halfrost-Field
✍️ 这里是写博客的地方 —— Halfrost-Field 冰霜之地
What-Uncertainties-Do-We-Need
Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"
MPAS-Plotting
References and Examples for Plotting MPAS Output
OpenSceneGraph
OpenSceneGraph git repository
ConcreteDropout
Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
Deep-Learning-Book-Chapter-Summaries
Attempting to make the Deep Learning Book easier to understand.
Coursera_deep_learning
This something about deep learning on Coursera by Andrew Ng
BayesianCNN
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015
char-rnn
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
LaTeX-Template-Cn
\LaTeX 中文模版收集。
variational_dropout
Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch