Supervised Deep Learning of Elastic SRV Distances on the Shape Space of Curves. - Emmanuel Hartman; Yashil Sukurdeep; Nicolas Charon; Eric Klassen; Martin Bauer 004 (CVPR Workshops, 2021)

VariGrad: A Novel Feature Vector Architecture for Geometric Deep Learning on Unregistered Data. - Emmanuel Hartman; Emery Pierson (3DOR (Short Papers), 2023)

BaRe-ESA: A Riemannian Framework for Unregistered Human Body Shapes. - Emmanuel Hartman; Emery Pierson; Martin Bauer 004; Nicolas Charon; Mohamed Daoudi (ICCV, 2023)

Elastic Shape Analysis of Surfaces with Second-Order Sobolev Metrics: A Comprehensive Numerical Framework. - Emmanuel Hartman; Yashil Sukurdeep; Eric Klassen; Nicolas Charon; Martin Bauer 004 (Int. J. Comput. Vis., 2023)

Learning from landmarks, curves, surfaces, and shapes in Geomstats. - Luís F. Pereira; Alice Le Brigant; Adele Myers; Emmanuel Hartman; Amil Khan; Malik Tuerkoen; Trey Dold; Mengyang Gu; Pablo Suárez-Serrato; Nina Miolane (CoRR, 2024)

Self Supervised Networks for Learning Latent Space Representations of Human Body Scans and Motions. - Emmanuel Hartman; Nicolas Charon; Martin Bauer 004 (CoRR, 2024)

Square Root Normal Fields for Lipschitz Surfaces and the Wasserstein Fisher Rao Metric. - Emmanuel Hartman; Martin Bauer 004; Eric Klassen (SIAM J. Math. Anal., 2024)

Basis Restricted Elastic Shape Analysis on the Space of Unregistered Surfaces. - Emmanuel Hartman; Emery Pierson; Martin Bauer 004; Mohamed Daoudi; Nicolas Charon (Int. J. Comput. Vis., 2025)

SVarM: Linear Support Varifold Machines for Classification and Regression on Geometric Data. - Emmanuel Hartman; Nicolas Charon (CoRR, 2025)