geomstats: a Python Package for Riemannian Geometry in Machine Learning. - Nina Miolane; Johan Mathe; Claire Donnat; Mikael Jorda; Xavier Pennec (CoRR, 2018)

PVNet: A LRCN Architecture for Spatio-Temporal Photovoltaic PowerForecasting from Numerical Weather Prediction. - Johan Mathe; Nina Miolane; Nicolas Sébastien; Jeremie Lequeux (CoRR, 2019)

Introduction to Geometric Learning in Python with Geomstats. - Nina Miolane; Nicolas Guigui; Hadi Zaatiti; Christian Shewmake; Hatem Hajri; Daniel Brooks; Alice Le Brigant; Johan Mathe; Benjamin Hou; Yann Thanwerdas; Stefan Heyder; Olivier Peltre; et al. (SciPy, 2020)

Geomstats: A Python Package for Riemannian Geometry in Machine Learning. - Nina Miolane; Alice Le Brigant; Johan Mathe; Benjamin Hou; Nicolas Guigui; Yann Thanwerdas; Stefan Heyder; Olivier Peltre; Niklas Koep; Hadi Zaatiti; Hatem Hajri; Yann Cabanes; et al. (CoRR, 2020)

ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results. - Nina Miolane; Matteo Caorsi; Umberto Lupo; Marius Guerard; Nicolas Guigui; Johan Mathe; Yann Cabanes; Wojciech Reise; Thomas Davies 001; António Leitão; Somesh Mohapatra; Saiteja Utpala; et al. (CoRR, 2021)

ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. - Adele Myers; Saiteja Utpala; Shubham Talbar; Sophia Sanborn; Christian Shewmake; Claire Donnat; Johan Mathe; Rishi Sonthalia; Xinyue Cui; Tom Szwagier; Arthur Pignet; Andri Bergsson; et al. (TAG-ML, 2022)

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. - Adele Myers; Saiteja Utpala; Shubham Talbar; Sophia Sanborn; Christian Shewmake; Claire Donnat; Johan Mathe; Umberto Lupo; Rishi Sonthalia; Xinyue Cui; Tom Szwagier; Arthur Pignet; et al. (CoRR, 2022)

ICML 2023 Topological Deep Learning Challenge: Design and Results. - Mathilde Papillon; Mustafa Hajij; Audun Myers; Florian Frantzen; Ghada Zamzmi; Helen Jenne; Johan Mathe; Josef Hoppe; Michael T. Schaub; Theodore Papamarkou; Aldo Guzmán-Sáenz; Bastian Rieck; et al. (TAG-ML, 2023)

ICML 2023 Topological Deep Learning Challenge : Design and Results. - Mathilde Papillon; Mustafa Hajij; Florian Frantzen; Josef Hoppe; Helen Jenne; Johan Mathe; Audun Myers; Theodore Papamarkou; Michael T. Schaub; Ghada Zamzmi; Tolga Birdal; Tamal K. Dey; et al. (CoRR, 2023)

The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks. - Simon Mataigne; Johan Mathe; Sophia Sanborn; Christopher Hillar; Nina Miolane (NeurIPS, 2024)

Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures. - Sophia Sanborn; Johan Mathe; Mathilde Papillon; Domas Buracas; Hansen Lillemark; Christian Shewmake; Abby Bertics; Xavier Pennec; Nina Miolane (CoRR, 2024)

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. - Guillermo Bernárdez; Lev Telyatnikov; Marco Montagna; Federica Baccini; Mathilde Papillon; Miquel Ferriol Galmés; Mustafa Hajij; Theodore Papamarkou; Maria Sofia Bucarelli; Olga Zaghen; Johan Mathe; Audun Myers; et al. (CoRR, 2024)