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)

Preface. - Sophia Sanborn; Christian Shewmake; Simone Azeglio; Arianna Di Bernardo; Nina Miolane (NeurReps, 2022)

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)

Group Equivariant Sparse Coding. - Christian Shewmake; Nina Miolane; Bruno A. Olshausen (GSI (1), 2023)

Bispectral Neural Networks. - Sophia Sanborn; Christian Shewmake; Bruno A. Olshausen; Christopher J. Hillar (ICLR, 2023)

Preface. - Sophia Sanborn; Christian Shewmake; Simone Azeglio; Nina Miolane (NeurReps, 2023)

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)

On the Utility of Equivariance and Symmetry Breaking in Deep Learning Architectures on Point Clouds. - Sharvaree P. Vadgama; Mohammad Mohaiminul Islam; Domas Buracus; Christian Shewmake; Erik J. Bekkers (CoRR, 2025)