#### Preprints

- Fast end-to-end learning on protein surfaces,

to be presented at CVPR 2021,

Freyr Sverrisson*, Jean Feydy*, Bruno Correia, Michael Bronstein, links: Paper, Code. - Kernel operations on the GPU, with autodiff, without memory overflows,

to appear in the Journal of Machine Learning Research,

Benjamin Charlier*, Jean Feydy*, Joan Glaunès*, François-David Collin, Ghislain Durif, links: Paper, Code. - Sinkhorn divergences for unbalanced Optimal Transport,

submitted in March 2021,

Thibault Séjourné, Jean Feydy, François-Xavier Vialard, Alain Trouvé, Gabriel Peyré, links: Paper, Code. - Collective proposal distributions for nonlinear MCMC samplers: mean-field theory and fast implementation,

Grégoire Clarté, Antoine Diez, Jean Feydy, links: Paper, Code.

#### PhD thesis

- Geometric data analysis, beyond convolutions,

Jean Feydy, under the supervision of Alain Trouvé.

Defended on July 2, 2020, in front of Xavier Pennec, Jean-David Benamou, Marc Niethammer, Pierre Alliez and Alexandre Gramfort.

Links: Official version, Thesis + Latex, Slides + Latex.

#### Conference Papers

- Fast geometric learning with symbolic matrices,

Jean Feydy*, Joan Glaunès*, Benjamin Charlier*, Michael Bronstein,

NeurIPS 2020 (spotlight presentation), links: Paper, Slides + Latex, Poster + Latex, Links and Videos, Website, Code. - Fast and scalable optimal transport for brain tractograms,

Jean Feydy*, Pierre Roussillon*, Alain Trouvé, Pietro Gori,

MICCAI 2019, links: Paper, Poster + PowerPoint, Website, Code. - Interpolating between optimal transport and MMD using Sinkhorn divergences,

Jean Feydy, Thibault Séjourné, François-Xavier Vialard, Shun-ichi Amari, Alain Trouvé, Gabriel Peyré,

AiStats 2019, links: Paper, Slides, Poster + Latex, Website, Code.

- Global divergences between measures: from Hausdorff distance to optimal transport,

Jean Feydy, Alain Trouvé,

ShapeMI 2018 (Miccai workshop, oral presentation), links: Paper, Slides + Latex, Code.

- Optimal transport for diffeomorphic registration,

Jean Feydy, Benjamin Charlier, François-Xavier Vialard, Gabriel Peyré,

MICCAI 2017 (oral presentation), links: Hal, Arxiv, Code, Slides (+videos), Poster, Latex.

- Distortion minimizing geodesic subspaces in shape spaces and computational anatomy,

Benjamin Charlier, Jean Feydy, David W. Jacobs and Alain Trouvé,

VipImage 2017.

#### Talks

- Fast geometric learning with symbolic matrices.

January 2021, CogSys seminar, DTU Compute (Online): Pdf, Latex.

December 2020, NeurIPS 2020 (Online): Spotlight presentation + Latex, Poster + Latex, Links and Videos. - Geometric data analysis, beyond convolutions.

April 2021, Signal Processing Laboratory (LTS4, EPFL, Online): Pdf, Latex.

March 2021, Image, Visual and Language Computing Seminar (UNC Chapel Hill, Online): Pdf, Latex.

January 2021, Centre de Vision Numérique (CentraleSupélec - Inria Saclay, Online): Pdf, Latex.

October 2020, Centre de Recherche des Cordeliers (Online) - in French: Pdf, Latex, Video.

September 2020, University College London (Online) - with more applications: Pdf, Latex, Video, Workshop.

July 2020, PhD defense (Online): Pdf, Latex.

December 2019, King's College London: Pdf, Latex. - L'imagerie médicale, un calcul structuré.

October 2020, Institut du Cerveau (Online): Pdf, Latex, Video, Conference. - Geometric loss functions for shape analysis

July 2020, SIAM Imaging Sciences 2020 (Online): Pdf, Video, Latex. - Sorting points in dimension D > 1.

April 2021, Sea Ice Modeling and Data Assimilation (Dartmouth, Online): Pdf, Latex.

February 2020, Twitter London: Pdf, Latex. - Discrete optimal transport: scaling up to 1M samples in 1s.

June 2019, "People in optimal transportation and applications" workshop, Cortona: Pdf, Latex. - Artificial "neural networks": what radiologists should know.

(French) Mai 2020, DIU Neuro-radiologie vieillissement (en ligne): Pdf, Video;

(English) June 2019, Harvey Cushing symposium (American Hospital of Paris):

Pdf 16:9, High-res pptx, Low-res pptx, LaTex source;

(French) Mars 2019, congrès de la Société Française de Neuro-Radiologie (Paris):

Pdf 16:9, High-res pptx, Low-res pptx, LaTex source;

(French) Juin 2018, congrès de la Société Française d'Imagerie Cardiaque et Vasculaire (Beaune):

Pdf 4:3, Latex + Code. - Robust matching of measures with Optimal Transport.

February 2019, GTTI, ENS Cachan: Pdf, Latex.

December 2018, BIRS center, Banff: Pdf, Latex.

November 2018, Télécom ParisTech: Pdf, Latex. - Global divergences between measures, from Hausdorff distance to Optimal Transport.

September 2018, ShapeMI workshop, MICCAI 2018 (Granada): Pdf, Latex + Code.

July 2018, Curves and Surfaces 2018 (Arcachon): Pdf, Latex + Code. - Normalizing LDDMM metrics using autodiff, an introduction to KeOps.

June 2018, SIAM Imaging Sciences 2018 (Bologna): Pdf, Latex + Code.

November 2017, Isaac Newton Institute (Cambridge): Pdf, Latex. - Automatic differentiation for applied mathematicians: presenting the PyTorch library.

February 2018, at the ENS Ulm, ENS Cachan and Jussieu (Paris VI): Pdf, Latex + Code. - Optimal transport for diffeomorphic registration: a global and robust data attachment term.

September 2017, MICCAI 2017, Québec City: Pdf (+videos), Poster, Latex.

June 2017, Asclepios Inria Team: Pdf, Latex. - Riemannian geometry for computational anatomy: presenting the LDDMM framework.

October 2017, ENS Department of Mathematics and Applications: Pdf, Full Latex.

June 2017, MoKaPlan Inria Team: Pdf (+videos), Latex.