Time series convolution. Website: https://spatiotemporal-data.github.io/posts/ts_conv

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

Machine learning for transportation data imputation and prediction.

Discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression. (IEEE TKDE'24)

Laplacian convolutional representation for traffic time series imputation. (IEEE TKDE'24)

Tensor decomposition for machine learning (w/ Python implementation)

Temporal matrix factorization for sparse traffic time series forecasting.

Visualizing spatial data with Python

Spatiotemporal climate variable data and their visualization.

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

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

LaTeX论文写作教程 (清华大学出版社)

Creating presentation slides by using Beamer in LaTeX.

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

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

Understanding urban mobility patterns of cycling with bikeshare data.

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

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

Geometric low-rank tensor completion for color image inpainting.

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

Kronecker product decomposition/approximation.

Research correction.

Low-rank tensor learning with PyTorch.

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

Low-rank tensor completion algorithm - HaLRTC.