Preprints

• Approximation and structured prediction with sparse Wasserstein barycenters, submitted in February 2022,
  Minh-Hieu Do, Jean Feydy, Olga Mula, 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.

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. I was awarded two PhD thesis awards by the AFRIF (French association for shape analysis and recognition) and the Chancellerie des Universités de Paris (édition 2021).
  Links: Official version, Thesis + Latex, Slides + Latex.

Journal Papers

• Collective proposal distributions for nonlinear MCMC samplers: mean-field theory and fast implementation,
  Grégoire Clarté, Antoine Diez, Jean Feydy,
  Electronic Journal of Statistics, 2022, links: Paper, Code.
• Kernel operations on the GPU, with autodiff, without memory overflows,
  Benjamin Charlier*, Jean Feydy*, Joan Glaunès*, François-David Collin, Ghislain Durif,
  Journal of Machine Learning Research, 2021, links: Abstract, Paper, Code.

Conference Papers

• Physics-informed deep neural network for rigid-body protein docking,
  Freyr Sverrisson, Jean Feydy, Joshua Southern, Michael M Bronstein, Bruno Correia,
  MLDD 2022 (ICLR workshop, spotlight presentation), links: Paper.
• Accurate point cloud registration with robust optimal transport,
  Zhengyang Shen*, Jean Feydy*, Peirong Liu, Ariel Hernán Curiale, Ruben San José Estépar, Raúl San José Estépar, Marc Niethammer,
  NeurIPS 2021, links: Paper, Latex, Code.
• Fast end-to-end learning on protein surfaces,
  Freyr Sverrisson*, Jean Feydy*, Bruno Correia, Michael Bronstein,
  CVPR 2021, links: Paper, Poster, Slides, Video, Code.
• 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.

Short Medical Papers

• Artificial intelligence in diagnostic and interventional radiology: Where are we now?
  Tom Boeken, Jean Feydy, Augustin Lecler, Philippe Soyer, Antoine Feydy, Maxime Barat, Loïc Duron,
  Diagnostic and Interventional Imaging, 2022, links: Paper.
• Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications,
  Maxime Lacroix, Theodore Aouad, Jean Feydy, David Biau, Frédérique Larousserie, Laure Fournier, Antoine Feydy,
  Diagnostic and Interventional Imaging, 2022, links: Paper.
• Accelerating high-dimensional temporal modelling using Graphics Processing Units for pharmacovigilance signal detection on real-life data,
  Pierre Sabatier, Jean Feydy, Anne-Sophie Jannot,
  Challenges of Trustable AI and Added-Value on Health, 2022, links: Paper.

Maths and CS Talks

• Computational optimal transport: mature tools and open problems.
  November 2022, Measure-theoretic approaches and optimal transportation in statistics, Institut Henri Poincaré: Pdf, Latex, workshop.
  August 2022, Workshop on mathematical imaging and surface processing, Oberwolfach: Pdf, Latex, workshop.
  July 2022, Frontiers in Design Representation, University of Maryland: Pdf, Latex, Tutorial (HTML), Summer school.
  June 2022, Curves and Surfaces 2022, Arcachon: Pdf, Latex.
  June 2022, University of Göttingen: Pdf, Latex.
• Fast libraries for geometric data analysis.
  May 2023, Healthcare AI grand round, Nvidia: Pdf, Latex.
  May 2023, Workshop on geometry/physics-informed neural networks, Thales: Pdf, Latex.
  February 2023, Machine Learning Coffee Seminar, Finnish Center for Artificial Intelligence: Pdf, Latex, Seminar.
  July 2022, online meeting with Nvidia: Pdf, Latex.
  May 2022, joint HeKA-Soda seminar, PariSanté Campus: Pdf, Latex.
• Fast geometric libraries for vision and data sciences.
  April 2022, DataShape seminar, Inria Saclay: Pdf, Latex.
  December 2021, GRAPES software and industrial workshop, Inria Sophia: Conference, Pdf, Latex.
  December 2021, AI and healthcare seminar, Centre de Recherche des Cordeliers: Pdf, Latex.
  November 2021, JCJC développement, Inria Saclay: Conference, Pdf, Latex.
  November 2021, Robotic Perception team, Université de Picardie Jules Verne, Amiens: Pdf, Latex.
  October 2021, GdR MIA, Institut Henri Poincaré: Conference, Pdf, Latex.
• Calcul géométrique rapide pour la vision et les sciences des données.
  September 2021, Orasis 2021, Lac de Saint-Ferréol: Conference, Pdf, Latex.
• 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.
• 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.
• 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.
• 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.

Radiology Talks

• Key tasks for AI in musculoskeletal imaging
  June 2023, ESSR 2023: Pdf, Pptx, Latex, Conference.
  
• Quels logiciels pour l'apprentissage en anatomie ?
  March 2023, IABM 2023, Institut Curie: Pdf, Latex, Conference.
  
• L'imagerie médicale, un calcul structuré.
  October 2020, Institut du Cerveau (Online): Pdf, Latex, Video, Conference.
• 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.

Miscellaneous Talks

• Présentation de l'équipe HeKA
  June 2023, Matinée Science à PariSanté Campus: Pdf, Pptx, Latex.
  
• Tools to write and publish your code
  June 2023, HeKA team seminar, PariSanté Campus: Pdf, Latex.
  
• Du calcul haute performance à l'hôpital ?
  May 2023, Séminaire Médecine et Mathématiques, Centre Borelli: Pdf, Latex.
  February 2023, Demi-heure de science, Inria Paris: Pdf, Latex.
  
• Getting started with clusters.
  January 2023, Team building seminar of the HeKA team, Rouen: Pdf, Latex.
  
• Retour sur le sondage auprès des utilisateurs des moyens de calcul Inria.
  June 2022, CEP Inria Paris: Pdf, Latex.
• Geometric data analysis for healthcare.
  May 2021, application for the Inria CRCN position (Inria Paris, online): Application, Slides (in French), Video, 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.
• 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.