Fei Ye's repositories
export_fig
A MATLAB toolbox for exporting publication quality figures
google-access-helper
谷歌访问助手破解版
markdown-here
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
pumpkin-book
《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book
pytorch-examples
Simple examples to introduce PyTorch
pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
shadowsocks-windows
If you want to keep a secret, you must also hide it from yourself.
Adaptive-Low-Rank-Tensor-Representation
Matlab implementation of TNNLS2019 paper " Accurate Tensor Completion via Adaptive Low-Rank Representation "
bptf
Bayesian Poisson tensor factorization
CPTPprojection
Completely positive and trace preserving projection for maximum likelihood process tomography. Subroutine for projected linear inversion and projected gradient descent. Prepint at https://arxiv.org/abs/1803.10062. Published version at
Demo_DFFN
The code implementation of our paper "Hyperspectral Image Classification With Deep Feature Fusion Network", TGRS, 2018.
FuVarRelease
codes for the paper "Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability", IEEE TIP 2020
Halfrost-Field
✍️ 这里是写博客的地方 —— Halfrost-Field 冰霜之地
Hyperspectral-Image-Super-Resolution-Benchmark
A list of hyperspectral image super-solution resources collected by Junjun Jiang
py_pansharpening
Rewrite some pansharpening methods with python
pyprobml
Python code for "Machine learning: a probabilistic perspective" (2nd edition)
Python-100-Days
Python - 100天从新手到大师
scikit-learn
scikit-learn: machine learning in Python
Truncated-Cauchy-Non-Negative-Matrix-Factorization
Non-negative matrix factorization (NMF) minimizes the euclidean distance between the data matrix and its low rank approximation, and it fails when applied to corrupted data because the loss function is sensitive to outliers. In this paper, we propose a Truncated CauchyNMF loss that handle outliers by truncating large errors, and develop a Truncated CauchyNMF to robustly learn the subspace on noisy datasets contaminated by outliers. We theoretically analyze the robustness of Truncated CauchyNMF comparing with the competing models and theoretically prove that Truncated CauchyNMF has a generalization bound which converges at a rate of order O(lnn/n‾‾‾‾‾√) , where n is the sample size. We evaluate Truncated CauchyNMF by image clustering on both simulated and real datasets. The experimental results on the datasets containing gross corruptions validate the effectiveness and robustness of Truncated CauchyNMF for learning robust subspaces.
TT-Toolbox
The git repository for the TT-Toolbox
ttpy
Python implementation of the TT-Toolbox
VegetationClassification
Python machine learning to classify forest/trees (vegetation) in multispectral, panchromatic satellite imagery.