SOFTWARE

Computations and statistics on manifolds with geometric structures: github.com/geomstats

• To get started with geomstats, see the examples directory and the notebooks directory.

• For more in-depth applications of geomstats, see the applications repository.

• The documentation of geomstats can be found on the documentation website.

• Contact us if you are interested in contributing!

• If you find geomstats useful, please kindly cite our paper:

  • Miolane, N. et al. Geomstats: An open-source Python package of Riemannian geometry in machine learning. (2020).

• If you want to stay up-to-date with geometric statistics and learning, follow our twitter-bot that surveys the literature for you.

• Co-organizers of hackathons for Riemannian geometry in Machine Learning (2019 - present), see for example SCAI Geomstats Hackathon.

• Lead organizer of the ICLR 2021 Challenge for Computational Geometry and Topology.

• Blog-post: Open Source bridges the gap between mathematical research and industry 2021.