(Toutes les publications doivent être déposées sur HAL avec licence CCBY)
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows
Clément Bonet, Christophe Vauthier, Anna Korba
In: International Conference on Machine Learning (ICML)
2025On the Wasserstein geodesic principal component analysis of probability measures
Nina Vesseron, Elsa Cazelles, Alice Le Brigant, Thierry Klein
2025Computing Barycentres of Measures for Generic Transport Costs
Eloi Tanguy, Julie Delon, Nathaël Gozlan
2025Explicit Universal and Approximate-Universal Kernels on Compact Metric Spaces
Eloi Tanguy
2025Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite, Nicolas Chesneau, Özgür Şimşek, Marc Schoenauer
2025A User's Guide to Sampling Strategies for Sliced Optimal Transport
Keanu Sisouk, Julie Delon, Julien Tierny
Journal: Transactions on Machine Learning Research Journal
2025Neural semi-Lagrangian method for high-dimensional advection-diffusion problems
Emmanuel Franck, Victor Michel-Dansac, Laurent Navoret, Vincent Vigon
2025Sample complexity of optimal transport barycenters with discrete support
Léo Portales, Edouard Pauwels, Elsa Cazelles
2025Convergence Analysis of a Proximal Stochastic Denoising Regularization Algorithm
Marien Renaud, Julien Hermant, Nicolas Papadakis
In: International Conference on Scale Space and Variational Methods in Computer Vision (SSVM'25)
2025A variational method for curve extraction
Majid Arthaud, Antonin Chambolle, Vincent Duval
In: SSVM 2025 - 10th Scale-Space and Variational Methods in Computer Vision
2025Towards optimal algorithms for the recovery of low-dimensional models with linear rates
Yann Traonmilin, Jean François Aujol, Antoine Guennec
2025On the Relation between Rectified Flows and Optimal Transport
Johannes Hertrich, Antonin Chambolle, Julie Delon
2025Gradient correlation is a key factor to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol, Charles Dossal, Aude Rondepierre
In: International Conference on Learning Representations, 2025
2025Stability of optimal transport maps on Riemannian manifolds
Jun Kitagawa, Cyril Letrouit, Quentin Merigot
2025Volume-Preserving Geometric Shape Optimization of the Dirichlet Energy Using Variational Neural Networks
Amaury Bélières--Frendo, Emmanuel Franck, Victor Michel-Dansac, Yannick Privat
Journal: Neural Networks
2025Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality Reduction
Mattéo Clémot, Julie Digne, Julien Tierny
2025LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimization
Alessio Spagnoletti, Jean Prost, Andrés Almansa, Nicolas Papadakis, Marcelo Pereyra
2025Differentiation of inertial methods for optimizing smooth parametric function
Jean-Jacques Godeme
2025Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemia
Erell Gachon, Jérémie Bigot, Elsa Cazelles, Audrey Bidet, Jean-Philippe Vial, Pierre-Yves Dumas, Aguirre Mimoun
Journal: Cytometry Part A
2025DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis
In: International Conference on Artificial Intelligence and Statistics (AISTATS)
2025Bilevel gradient methods and Morse parametric qualification
Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter
2025Scalable and consistent embedding of probability measures into Hilbert spaces via measure quantization
Erell Gachon, Jérémie Bigot, Elsa Cazelles
2025Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance
Christophe Vauthier, Quentin Merigot, Anna Korba
2025Study of the behaviour of Nesterov Accelerated Gradient in a non convex setting: the strongly quasar convex case
Julien Hermant, Jean-François Aujol, Charles Dossal, Aude Rondepierre
2025Image = Cartoon+Texture: How Yves Meyer's "Oscillating patterns in image processing and in some nonlinear evolution equations" ended up in a computer vision model
Antonin Chambolle, Jean-Michel Morel
2025Gluing methods for quantitative stability of optimal transport maps
Cyril Letrouit, Quentin Mérigot
2025Accelerating the convergence of Newton's method for nonlinear elliptic PDEs using Fourier neural operators
Joubine Aghili, Romain Hild, Victor Michel-Dansac, Vincent Vigon, Emmanuel Franck
Journal: Communications in Nonlinear Science and Numerical Simulation
2025Audio signal interpolation using optimal transportation of spectrograms
David Valdivia, Marien Renaud, Elsa Cazelles, Cédric Févotte
In: IEEE Workshop on Statistical Signal Processing (SSP)
2025Volume Preserving Neural Shape Morphing
Camille Buonomo, Julie Digne, Raphaëlle Chaine
Journal: Computer Graphics Forum
2025A Cahn--Hilliard--Willmore phase field model for non-oriented interfaces
Élie Bretin, Antonin Chambolle, Simon Masnou
2024Statistical and Geometrical Properties of Regularized Kernel Kullback-Leibler Divergence
Clémentine Chazal, Anna Korba, Francis Bach
In: Neurips 2024 - 38th Conference on Neural Information Processing Systems
2024Mirror and Preconditioned Gradient Descent in Wasserstein Space
Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba
In: Neural Information Processing Systems (NeurIPS)
2024Bayesian Deconvolution of Astronomical Images with Diffusion Models: Quantifying Prior-Driven Features in Reconstructions
Alessio Spagnoletti, Alexandre Boucaud, Marc Huertas-Company, Wassim Kabalan, Biswajit Biswas
In: 38th conference on Neural Information Processing Systems
2024Differentiable Owen Scrambling
Bastien Doignies, David Coeurjolly, Nicolas Bonneel, Julie Digne, Jean-Claude Iehl, Victor Ostromoukhov
Journal: ACM Transactions on Graphics
2024Joint structure-texture low dimensional modeling for image decomposition with a plug and play framework
Antoine Guennec, Jean-François Aujol, Yann Traonmilin
2024Reconstructing discrete measures from projections. Consequences on the empirical Sliced Wasserstein Distance
Eloi Tanguy, Rémi Flamary, Julie Delon
Journal: Comptes Rendus. Mathématique
2024Optimization with First Order Algorithms
Charles Dossal, Samuel Hurault, Nicolas Papadakis
2024Complexity Analysis of Regularization Methods for Implicitly Constrained Least Squares
Akwum Onwunta, Clément Royer
Journal: Journal of Scientific Computing
2024Inclusion and estimates for the jumps of minimizers in variational denoising
Antonin Chambolle, Michał Łasica
Journal: SIAM Journal on Imaging Sciences
2024Constrained Approximate Optimal Transport Maps
Eloi Tanguy, Agnès Desolneux, Julie Delon
2024control-toolbox: solving control problems within Julia
Joseph Gergaud, Jean-Baptiste Caillau, Olivier Cots, Pierre Martinon
In: FGS 2024 - 21st French-German-Spanish conferences on Optimization
2024On the sequential convergence of Lloyd's algorithms
Léo Portales, Elsa Cazelles, Edouard Pauwels
Journal: Mathematics of Operations Research
2024Robust risk management via multi-marginal optimal transport
Hamza Ennaji, Quentin Mérigot, Luca Nenna, Brendan Pass
Journal: Journal of Optimization Theory and Applications
2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
Marien Renaud, Jiaming Liu, Valentin de Bortoli, Andrés Almansa, Ulugbek Kamilov
In: (ICLR 2024) The Twelfth International Conference on Learning Representations
2024Discrete-to-continuous crystalline curvature flows
Antonin Chambolle, Daniele de Gennaro, Massimiliano Morini
2024Convergence of SGD for Training Neural Networks with Sliced Wasserstein Losses
Eloi Tanguy
2024Heavy Ball Momentum for Non-Strongly Convex Optimization
Jean-François Aujol, Charles Dossal, Hippolyte Labarrière, Aude Rondepierre
2024Solving optimal control problems with Julia
Jean-Baptiste Caillau, Olivier Cots, Joseph Gergaud, Pierre Martinon
In: Julia and Optimization Days 2023
2023Properties of Discrete Sliced Wasserstein Losses
Eloi Tanguy, Rémi Flamary, Julie Delon
Journal: Mathematics of Computation
2023