The repository contains the code of the probabilistic geometric principal component analysis (PGPCA) algorithm.
Due to the file size, please download the matfile PGPCA_Simu_T2_3D_ICLR.mat (175 MB) including the sample data from the supplementary material in OpenReview.
PGPCA has been published at the International Conference on Learning Representations (ICLR) in 2025.
@inproceedings{hsieh2025probabilistic,
title={Probabilistic Geometric Principal Component Analysis with application to neural data},
author={Han-Lin Hsieh and Maryam Shanechi},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=mkDam1xIzW}
}
Copyright (c) 2025 University of Southern California
See full notice in LICENSE.md
Han-Lin Hsieh and Maryam M. Shanechi
Shanechi Lab, University of Southern California