xinychen

latex-cookbook

LaTeX论文写作教程 (清华大学出版社)

awesome-latex-drawing

Drawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.

transdim

Machine learning for transportation data imputation and prediction.

tensor-learning

Python codes for low-rank tensor factorization, tensor completion, and tensor regression techniques.

academic-drawing

Providing codes (including Matlab and Python) for visualizing numerical experiment results.

awesome-beamer

Creating presentation slides by using Beamer in LaTeX.

tensor-book

张量计算系列教程 (Tensor Computations Tutorials)

tracebase

Nonstationary temporal matrix factorization for sparse traffic time series forecasting.

geotensor

Geometric low-rank tensor completion for color image inpainting.

vars

Discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression. (IEEE TKDE'23)

fluid-inpainting

Inpainting Fluid Dynamics with Tensor Decomposition (NumPy). Blog post: https://medium.com/p/d84065fead4d

mob4cast

Multidimensional time series prediction with passenger/taxi flow data sets.

autoregressive-tensor

Low-rank autoregressive tensor completion for spatiotemporal traffic data imputation. (IEEE TITS'22)

tensor_completion

Low-rank tensor completion algorithm - HaLRTC.

visual-spatial-data

Visualizing spatial data with Python (Python空间数据可视化).

conjugate-gradient

Some simple examples for showing how does conjugate gradient method work on the system of linear equations. Blog post: https://medium.com/p/7f16cbae18a3

climate-tensor

Spatiotemporal climate variable data and their visualization.

TensorPi

Low-rank tensor learning with PyTorch.

xinychen

xinychen.github.io

Personal website

fluid-forecasting

Forecasting fluid dynamics with temporal matrix factorization in the presence of missing values.

tensor-var

Kronecker product decomposition/approximation.

cycling

Understanding urban mobility patterns of cycling with bikeshare data.

Newton-Raphson

Some simple and intuitive examples for showing how does the Newton-Raphson algorithm work for finding the root of equations.

research.correction

Research correction.