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FTMAL-paper

This is the companion repository to the paper Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats by Nicolas Guigui, Nina Miolane and Xavier Pennec, to appear in Foundations and Trends in Machine Learning in Januray 2023.

The goal of this repo is to keep updated all the code samples from the paper to ensure compatibility with future releases of the geomstats package.

Follow the geomstats install guidelines to get started. This repo has been tested with geomstats version 2.5.0.

Feel free to open an issue or contact us if you have any questions or comment!

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