Code & Data

We develop the PyKale library in the PyTorch ecosystem to make machine learning more accessible to interdisciplinary research by bridging gaps between data, software, and end users.

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The Matlab code of algorithms and related data from my earlier works.

1. Remurs (Regularized Multilinear Regression and Selection): Remurs Version 1.0: code, data, and paper (2.85MB)
2. UMLDA (Uncorrelated Multilinear Discriminant Analysis): UMLDA Version 1.1: code, data, and paper (19.73MB)
3. RCSP (Regularized Common Spatial Pattern): RCSP Version 1.0: code and paper (2.19MB)
4. UMPCA (Uncorrelated Multilinear Principal Component Analysis): UMPCA Version 1.0: code, data, and paper (7.87MB)
5. MPCA (Multilinear Principal Component Analysis): MPCA Version 1.3 package: code, data, samples, and paper (5.18MB)
   Gait data: 128x88x20(21.2M); 64x44x20(9.9M); 32x22x10(3.2M)
6. Binary Image Watermarking/Data Hiding: Binary Image Watermarking/Data Hiding: Data, Algorithms, and Distortion Measure (3.7MB)