Coronary Motion Estimation from CTA Using Probability Atlas and Diffeomorphic Registration. - Dong Ping Zhang; Laurent Risser; François-Xavier Vialard; Philip J. Edwards; Coert Metz; Lisan Neefjes; Nico Mollet; Wiro J. Niessen; Daniel Rueckert (MIAR, 2010)

Simultaneous Fine and Coarse Diffeomorphic Registration: Application to Atrophy Measurement in Alzheimer's Disease. - Laurent Risser; François-Xavier Vialard; Robin Wolz; Darryl D. Holm; Daniel Rueckert (MICCAI (2), 2010)

Large Deformation Diffeomorphic Registration Using Fine and Coarse Strategies. - Laurent Risser; François-Xavier Vialard; Maria Murgasova; Darryl D. Holm; Daniel Rueckert (WBIR, 2010)

Geodesic Regression for Image Time-Series. - Marc Niethammer; Yang Huang; François-Xavier Vialard (MICCAI (2), 2011)

Diffeomorphic Atlas Estimation using Karcher Mean and Geodesic Shooting on Volumetric Images. - François-Xavier Vialard; Laurent Risser; Darryl D. Holm; Daniel Rueckert (MIUA, 2011)

Simultaneous Multi-scale Registration Using Large Deformation Diffeomorphic Metric Mapping. - Laurent Risser; François-Xavier Vialard; Robin Wolz; Maria Murgasova; Darryl D. Holm; Daniel Rueckert (IEEE Trans. Medical Imaging, 2011)

Local vs Global Descriptors of Hippocampus Shape Evolution for Alzheimer's Longitudinal Population Analysis. - Jean-Baptiste Fiot; Laurent Risser; Laurent D. Cohen; Jurgen Fripp; François-Xavier Vialard (STIA, 2012)

Diffeomorphic 3D Image Registration via Geodesic Shooting Using an Efficient Adjoint Calculation. - François-Xavier Vialard; Laurent Risser; Daniel Rueckert; Colin J. Cotter (Int. J. Comput. Vis., 2012)

Invariant Higher-Order Variational Problems II. - François Gay-Balmaz; Darryl D. Holm; David M. Meier; Tudor S. Ratiu; François-Xavier Vialard (J. Nonlinear Sci., 2012)

Mixture of Kernels and Iterated Semidirect Product of Diffeomorphisms Groups. - Martins Bruveris; Laurent Risser; François-Xavier Vialard (Multiscale Model. Simul., 2012)

Left-Invariant Metrics for Diffeomorphic Image Registration with Spatially-Varying Regularisation. - Tanya Schmah; Laurent Risser; François-Xavier Vialard (MICCAI (1), 2013)

Piecewise-diffeomorphic image registration: Application to the motion estimation between 3D CT lung images with sliding conditions. - Laurent Risser; François-Xavier Vialard; Habib Y. Baluwala; Julia A. Schnabel (Medical Image Anal., 2013)

Spatially-Varying Metric Learning for Diffeomorphic Image Registration: A Variational Framework. - François-Xavier Vialard; Laurent Risser (MICCAI (1), 2014)

Splines for diffeomorphisms. - Nikhil Singh 002; François-Xavier Vialard; Marc Niethammer (Medical Image Anal., 2015)

Quantum Optimal Transport for Tensor Field Processing. - Gabriel Peyré; Lenaïc Chizat; François-Xavier Vialard; Justin Solomon 001 (CoRR, 2016)

Geodesics on Shape Spaces with Bounded Variation and Sobolev Metrics. - Giacomo Nardi; Gabriel Peyré; François-Xavier Vialard (SIAM J. Imaging Sci., 2016)

Optimal Transport for Diffeomorphic Registration. - Jean Feydy; Benjamin Charlier; François-Xavier Vialard; Gabriel Peyré (MICCAI (1), 2017)

An Interpolating Distance Between Optimal Transport and Fisher-Rao Metrics. - Lenaïc Chizat; Gabriel Peyré; Bernhard Schmitzer; François-Xavier Vialard (Found. Comput. Math., 2018)

Scaling algorithms for unbalanced optimal transport problems. - Lenaïc Chizat; Gabriel Peyré; Bernhard Schmitzer; François-Xavier Vialard (Math. Comput., 2018)

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)

Metric Learning for Image Registration. - Marc Niethammer; Roland Kwitt; François-Xavier Vialard (CVPR, 2019)

Region-specific Diffeomorphic Metric Mapping. - Zhengyang Shen; François-Xavier Vialard; Marc Niethammer (NeurIPS, 2019)

Nonlinear model reduction on metric spaces. Application to one-dimensional conservative PDEs in Wasserstein spaces. - Virginie Ehrlacher; Damiano Lombardi; Olga Mula; François-Xavier Vialard (CoRR, 2019)

Sinkhorn Divergences for Unbalanced Optimal Transport. - Thibault Séjourné; Jean Feydy; François-Xavier Vialard; Alain Trouvé; Gabriel Peyré (CoRR, 2019)

Second-Order Models for Optimal Transport and Cubic Splines on the Wasserstein Space. - Jean-David Benamou; Thomas O. Gallouët; François-Xavier Vialard (Found. Comput. Math., 2019)

Faster Wasserstein Distance Estimation with the Sinkhorn Divergence. - Lénaïc Chizat; Pierre Roussillon; Flavien Léger; François-Xavier Vialard; Gabriel Peyré (NeurIPS, 2020)

A shooting formulation of deep learning. - François-Xavier Vialard; Roland Kwitt; Susan Wei; Marc Niethammer (NeurIPS, 2020)

A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation. - Adrien Vacher; Boris Muzellec; Alessandro Rudi; Francis R. Bach; François-Xavier Vialard (COLT, 2021)

ICON: Learning Regular Maps Through Inverse Consistency. - Thomas Hastings Greer; Roland Kwitt; François-Xavier Vialard; Marc Niethammer (ICCV, 2021)

The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation. - Thibault Séjourné; François-Xavier Vialard; Gabriel Peyré (NeurIPS, 2021)

Near-optimal estimation of smooth transport maps with kernel sums-of-squares. - Boris Muzellec; Adrien Vacher; Francis R. Bach; François-Xavier Vialard; Alessandro Rudi (CoRR, 2021)

Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe. - Thibault Séjourné; François-Xavier Vialard; Gabriel Peyré (AISTATS, 2022)

On global convergence of ResNets: From finite to infinite width using linear parameterization. - Raphaël Barboni; Gabriel Peyré; François-Xavier Vialard (NeurIPS, 2022)

Parameter tuning and model selection in Optimal Transport with semi-dual Brenier formulation. - Adrien Vacher; François-Xavier Vialard (NeurIPS, 2022)

GradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency. - Lin Tian 001; Thomas Hastings Greer; François-Xavier Vialard; Roland Kwitt; Raúl San José Estépar; Marc Niethammer (CoRR, 2022)

Unbalanced Optimal Transport, from Theory to Numerics. - Thibault Séjourné; Gabriel Peyré; François-Xavier Vialard (CoRR, 2022)

GradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency. - Lin Tian 001; Thomas Hastings Greer; François-Xavier Vialard; Roland Kwitt; Raúl San José Estépar; Richard Jarrett Rushmore; Nikolaos Makris; Sylvain Bouix; Marc Niethammer (CVPR, 2023)

Semi-Dual Unbalanced Quadratic Optimal Transport: fast statistical rates and convergent algorithm. - Adrien Vacher; François-Xavier Vialard (ICML, 2023)

Inverse Consistency by Construction for Multistep Deep Registration. - Thomas Hastings Greer; Lin Tian 001; François-Xavier Vialard; Roland Kwitt; Sylvain Bouix; Raúl San José Estépar; Richard J. Rushmore; Marc Niethammer (MICCAI (10), 2023)

uniGradICON: A Foundation Model for Medical Image Registration. - Lin Tian 001; Thomas Hastings Greer; Roland Kwitt; François-Xavier Vialard; Raúl San José Estépar; Sylvain Bouix; Richard J. Rushmore; Marc Niethammer (MICCAI (2), 2024)

MultiGradICON: A Foundation Model for Multimodal Medical Image Registration. - Basar Demir; Lin Tian 001; Thomas Hastings Greer; Roland Kwitt; François-Xavier Vialard; Raúl San José Estépar; Sylvain Bouix; Richard J. Rushmore; Ebrahim Ebrahim; Marc Niethammer (WBIR, 2024)

Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport. - Raphaël Barboni; Gabriel Peyré; François-Xavier Vialard (CoRR, 2024)

Toric geometry of entropic regularization. - Bernd Sturmfels; Simon Telen; François-Xavier Vialard; Max von Renesse (J. Symb. Comput., 2024)

Optimal Estimation of Smooth Transport Maps with Kernel SoS. - Adrien Vacher; Boris Muzellec; Francis R. Bach; François-Xavier Vialard; Alessandro Rudi (SIAM J. Math. Data Sci., 2024)

CARL: A Framework for Equivariant Image Registration. - Thomas Hastings Greer; Lin Tian 001; François-Xavier Vialard; Roland Kwitt; Raúl San José Estépar; Marc Niethammer (CVPR, 2025)

On the Global Convergence of Wasserstein Gradient Flow of the Coulomb Discrepancy. - Siwan Boufadene; François-Xavier Vialard (SIAM J. Math. Anal., 2025)

Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime. - Raphaël Barboni; Gabriel Peyré; François-Xavier Vialard (CoRR, 2025)

On the Existence of Monge Maps for the Gromov-Wasserstein Problem. - Théo Dumont; Théo Lacombe; François-Xavier Vialard (Found. Comput. Math., 2025)