Gabriel Peyré

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 103

Top Venues

Publications

Raphaël Barboni, Gabriel Peyré, François-Xavier Vialard
Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport. CoRR (2024)
Zhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin
Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization. CoRR (2024)
Othmane Sebbouh, Marco Cuturi, Gabriel Peyré
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport. AISTATS (2024)
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows. CoRR (2024)
Francisco Andrade, Gabriel Peyré, Clarice Poon
Sparsistency for inverse optimal transport. ICLR (2024)
Michael E. Sander, Raja Giryes, Taiji Suzuki, Mathieu Blondel, Gabriel Peyré
How do Transformers perform In-Context Autoregressive Learning? CoRR (2024)
Zhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin
Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization. AISTATS (2024)
Clarice Poon, Nicolas Keriven, Gabriel Peyré
The Geometry of Off-the-Grid Compressed Sensing. Found. Comput. Math. 23 (1) (2023)
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Abide by the Law and Follow the Flow: Conservation Laws for Gradient Flows. CoRR (2023)
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Abide by the law and follow the flow: conservation laws for gradient flows. NeurIPS (2023)
Michael E. Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. CoRR (2023)
Othmane Sebbouh, Marco Cuturi, Gabriel Peyré
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport. CoRR (2023)
Zaccharie Ramzi, Pierre Ablin, Gabriel Peyré, Thomas Moreau
Test like you Train in Implicit Deep Learning. CoRR (2023)
Clarice Poon, Gabriel Peyré
Smooth over-parameterized solvers for non-smooth structured optimization. Math. Program. 201 (1) (2023)
Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. ICML (2023)
Valérie Castin, Pierre Ablin, Gabriel Peyré
Understanding the Regularity of Self-Attention with Optimal Transport. CoRR (2023)
Thibault Séjourné, François-Xavier Vialard, Gabriel Peyré
Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe. AISTATS (2022)
Raphaël Barboni, Gabriel Peyré, François-Xavier Vialard
On global convergence of ResNets: From finite to infinite width using linear parameterization. NeurIPS (2022)
Meyer Scetbon, Gabriel Peyré, Marco Cuturi
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. ICML (2022)
Geert-Jan Huizing, Laura Cantini, Gabriel Peyré
Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors. ICML (2022)
Thibault Séjourné, François-Xavier Vialard, Gabriel Peyré
Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe. CoRR (2022)
Geert-Jan Huizing, Gabriel Peyré, Laura Cantini
Optimal transport improves cell-cell similarity inference in single-cell omics data. Bioinform. 38 (8) (2022)
Pierre Ablin, Gabriel Peyré
Fast and accurate optimization on the orthogonal manifold without retraction. AISTATS (2022)
Othmane Sebbouh, Marco Cuturi, Gabriel Peyré
Randomized Stochastic Gradient Descent Ascent. AISTATS (2022)
Clarice Poon, Gabriel Peyré
Smooth over-parameterized solvers for non-smooth structured optimization. CoRR (2022)
Thibault Séjourné, Gabriel Peyré, François-Xavier Vialard
Unbalanced Optimal Transport, from Theory to Numerics. CoRR (2022)
Michael E. Sander, Pierre Ablin, Gabriel Peyré
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? CoRR (2022)
Michael E. Sander, Pierre Ablin, Gabriel Peyré
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? NeurIPS (2022)
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré
Sinkformers: Transformers with Doubly Stochastic Attention. AISTATS (2022)
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré
Momentum Residual Neural Networks. CoRR (2021)
Clarice Poon, Gabriel Peyré
Smooth Bilevel Programming for Sparse Regularization. CoRR (2021)
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Low-Rank Sinkhorn Factorization. ICML (2021)
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré
Momentum Residual Neural Networks. ICML (2021)
Clarice Poon, Gabriel Peyré
Smooth Bilevel Programming for Sparse Regularization. NeurIPS (2021)
Raphaël Barboni, Gabriel Peyré, François-Xavier Vialard
Global convergence of ResNets: From finite to infinite width using linear parameterization. CoRR (2021)
Geert-Jan Huizing, Laura Cantini, Gabriel Peyré
Unsupervised Ground Metric Learning using Wasserstein Eigenvectors. CoRR (2021)
Othmane Sebbouh, Marco Cuturi, Gabriel Peyré
Randomized Stochastic Gradient Descent Ascent. CoRR (2021)
Meyer Scetbon, Gabriel Peyré, Marco Cuturi
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. CoRR (2021)
Matthieu Heitz, Nicolas Bonneel, David Coeurjolly, Marco Cuturi, Gabriel Peyré
Ground Metric Learning on Graphs. J. Math. Imaging Vis. 63 (1) (2021)
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré
Sinkformers: Transformers with Doubly Stochastic Attention. CoRR (2021)
Pierre Ablin, Gabriel Peyré
Fast and accurate optimization on the orthogonal manifold without retraction. CoRR (2021)
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Low-Rank Sinkhorn Factorization. CoRR (2021)
Thibault Séjourné, François-Xavier Vialard, Gabriel Peyré
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation. NeurIPS (2021)
Pierre Ablin, Gabriel Peyré, Thomas Moreau
Super-efficiency of automatic differentiation for functions defined as a minimum. ICML (2020)
Hicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form. NeurIPS (2020)
Pierre Ablin, Gabriel Peyré, Thomas Moreau
Super-efficiency of automatic differentiation for functions defined as a minimum. CoRR (2020)
Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra
Wasserstein Control of Mirror Langevin Monte Carlo. COLT (2020)
Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag
Distribution-Based Invariant Deep Networks for Learning Meta-Features. CoRR (2020)
Arthur Mensch, Gabriel Peyré
Online Sinkhorn: Optimal Transport distances from sample streams. NeurIPS (2020)
Lénaïc Chizat, Pierre Roussillon, Flavien Léger, François-Xavier Vialard, Gabriel Peyré
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence. NeurIPS (2020)
Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra
Wasserstein Control of Mirror Langevin Monte Carlo. CoRR (2020)
Jean-François Aujol, Jalal Fadili, Michael Hintermüller, Gabriel Peyré, Gerlind Plonka-Hoch, Gabriele Steidl
Guest Editorial JMIV Special Issue Mathematics and Image Analysis (MIA). J. Math. Imaging Vis. 61 (5) (2019)
Jalal Fadili, Guillaume Garrigos, Jérôme Malick, Gabriel Peyré
Model Consistency for Learning with Mirror-Stratifiable Regularizers. AISTATS (2019)
Gabriel Peyré, Marco Cuturi
Computational Optimal Transport. Found. Trends Mach. Learn. 11 (5-6) (2019)
Paul Catala, Vincent Duval, Gabriel Peyré
A Low-Rank Approach to Off-the-Grid Sparse Superresolution. SIAM J. Imaging Sci. 12 (3) (2019)
Nicolas Keriven, Gabriel Peyré
Universal Invariant and Equivariant Graph Neural Networks. CoRR (2019)
Arthur Mensch, Mathieu Blondel, Gabriel Peyré
Geometric Losses for Distributional Learning. CoRR (2019)
Gwendoline de Bie, Gabriel Peyré, Marco Cuturi
Stochastic Deep Networks. ICML (2019)
Clarice Poon, Gabriel Peyré
MultiDimensional Sparse Super-Resolution. SIAM J. Math. Anal. 51 (1) (2019)
Clarice Poon, Gabriel Peyré
Degrees of freedom for off-the-grid sparse estimation. CoRR (2019)
Matthieu Heitz, Nicolas Bonneel, David Coeurjolly, Marco Cuturi, Gabriel Peyré
Ground Metric Learning on Graphs. CoRR (2019)
Arthur Mensch, Mathieu Blondel, Gabriel Peyré
Geometric Losses for Distributional Learning. ICML (2019)
Nicolas Keriven, Gabriel Peyré
Universal Invariant and Equivariant Graph Neural Networks. NeurIPS (2019)
Aude Genevay, Lénaïc Chizat, Francis R. Bach, Marco Cuturi, Gabriel Peyré
Sample Complexity of Sinkhorn Divergences. AISTATS (2019)
Jean Feydy, Thibault Séjourné, François-Xavier Vialard, Shun-ichi Amari, Alain Trouvé, Gabriel Peyré
Interpolating between Optimal Transport and MMD using Sinkhorn Divergences. AISTATS (2019)
Thibault Séjourné, Jean Feydy, François-Xavier Vialard, Alain Trouvé, Gabriel Peyré
Sinkhorn Divergences for Unbalanced Optimal Transport. CoRR (2019)
Clarice Poon, Nicolas Keriven, Gabriel Peyré
Support Localization and the Fisher Metric for off-the-grid Sparse Regularization. AISTATS (2019)
Lenaïc Chizat, Gabriel Peyré, Bernhard Schmitzer, François-Xavier Vialard
An Interpolating Distance Between Optimal Transport and Fisher-Rao Metrics. Found. Comput. Math. 18 (1) (2018)
Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck
Wasserstein Dictionary Learning: Optimal Transport-Based Unsupervised Nonlinear Dictionary Learning. SIAM J. Imaging Sci. 11 (1) (2018)
Jalal Fadili, Jérôme Malick, Gabriel Peyré
Sensitivity Analysis for Mirror-Stratifiable Convex Functions. SIAM J. Optim. 28 (4) (2018)
Aude Genevay, Gabriel Peyré, Marco Cuturi
Learning Generative Models with Sinkhorn Divergences. AISTATS (2018)
Samuel Vaiter, Gabriel Peyré, Jalal Fadili
Model Consistency of Partly Smooth Regularizers. IEEE Trans. Inf. Theory 64 (3) (2018)
Clarice Poon, Nicolas Keriven, Gabriel Peyré
Support Localization and the Fisher Metric for off-the-grid Sparse Regularization. CoRR (2018)
Lenaïc Chizat, Gabriel Peyré, Bernhard Schmitzer, François-Xavier Vialard
Scaling algorithms for unbalanced optimal transport problems. Math. Comput. 87 (314) (2018)
Marco Cuturi, Gabriel Peyré
Semidual Regularized Optimal Transport. SIAM Rev. 60 (4) (2018)
Marco Cuturi, Gabriel Peyré
Semi-dual Regularized Optimal Transport. CoRR (2018)
Clarice Poon, Nicolas Keriven, Gabriel Peyré
A Dual Certificates Analysis of Compressive Off-the-Grid Recovery. CoRR (2018)
Gwendoline de Bie, Gabriel Peyré, Marco Cuturi
Stochastic Deep Networks. CoRR (2018)
Jonathan Vacher, Andrew Isaac Meso, Laurent U. Perrinet, Gabriel Peyré
Bayesian Modeling of Motion Perception Using Dynamical Stochastic Textures. Neural Comput. 30 (12) (2018)
Jingwei Liang, Jalal Fadili, Gabriel Peyré
Local Convergence Properties of Douglas-Rachford and Alternating Direction Method of Multipliers. J. Optim. Theory Appl. 172 (3) (2017)
Jalal Fadili, Gitta Kutyniok, Gabriel Peyré, Gerlind Plonka-Hoch, Gabriele Steidl
JMIV Special Issue Mathematics and Image Analysis. J. Math. Imaging Vis. 59 (3) (2017)
Jalal Fadili, Jérôme Malick, Gabriel Peyré
Sensitivity Analysis for Mirror-Stratifiable Convex Functions. CoRR (2017)
Jean Feydy, Benjamin Charlier, François-Xavier Vialard, Gabriel Peyré
Optimal Transport for Diffeomorphic Registration. MICCAI (1) (2017)
Jingwei Liang, Jalal Fadili, Gabriel Peyré
Activity Identification and Local Linear Convergence of Forward-Backward-type Methods. SIAM J. Optim. 27 (1) (2017)
Guillaume Carlier, Vincent Duval, Gabriel Peyré, Bernhard Schmitzer
Convergence of Entropic Schemes for Optimal Transport and Gradient Flows. SIAM J. Math. Anal. 49 (2) (2017)
Paul Catala, Vincent Duval, Gabriel Peyré
A Low-Rank Approach to Off-The-Grid Sparse Deconvolution. CoRR (2017)
Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck
Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning. CoRR (2017)
Justin Solomon, Gabriel Peyré, Vladimir G. Kim, Suvrit Sra
Entropic metric alignment for correspondence problems. ACM Trans. Graph. 35 (4) (2016)
Gabriel Peyré, Marco Cuturi, Justin Solomon
Gromov-Wasserstein Averaging of Kernel and Distance Matrices. ICML (2016)
Kévin Degraux, Gabriel Peyré, Jalal Fadili, Laurent Jacques
Sparse Support Recovery with Non-smooth Loss Functions. CoRR (2016)
Giacomo Nardi, Gabriel Peyré, François-Xavier Vialard
Geodesics on Shape Spaces with Bounded Variation and Sobolev Metrics. SIAM J. Imaging Sci. 9 (1) (2016)
Jingwei Liang, Jalal Fadili, Gabriel Peyré
Convergence rates with inexact non-expansive operators. Math. Program. 159 (1-2) (2016)
Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach
Stochastic Optimization for Large-scale Optimal Transport. CoRR (2016)
Guillaume Tartavel, Gabriel Peyré, Yann Gousseau
Wasserstein Loss for Image Synthesis and Restoration. SIAM J. Imaging Sci. 9 (4) (2016)
Jingwei Liang, Jalal Fadili, Gabriel Peyré
A Multi-step Inertial Forward-Backward Splitting Method for Non-convex Optimization. NIPS (2016)
Antoine Rolet, Marco Cuturi, Gabriel Peyré
Fast Dictionary Learning with a Smoothed Wasserstein Loss. AISTATS (2016)
Gabriel Peyré, Lenaïc Chizat, François-Xavier Vialard, Justin Solomon
Quantum Optimal Transport for Tensor Field Processing. CoRR (2016)
Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach
Stochastic Optimization for Large-scale Optimal Transport. NIPS (2016)
Nicolas Bonneel, Gabriel Peyré, Marco Cuturi
Wasserstein barycentric coordinates: histogram regression using optimal transport. ACM Trans. Graph. 35 (4) (2016)
Vinayak Abrol, Olivier Absil, Pierre-Antoine Absil, Sandrine Anthoine, Philippe Antoine, Thomas Arildsen, Nancy Bertin, Folkert Bleichrodt, Jérôme Bobin, Anne Bol, Antoine Bonnefoy, Francesco Caltagirone, Valerio Cambareri, Cecile Chenot, Vladimir S. Crnojevic, Marie Danková, Kévin Degraux, Jens Eisert, Mohamed-Jalal Fadili, Marylou Gabrié, Nicolas Gac, Daniele Giacobello, Carlos A. Gomez Gonzalez, Adriana Gonzalez, Pierre-Yves Gousenbourger, Mads Græsbøll Christensen, Rémi Gribonval, Stéphanie Guérit, Shaoguang Huang, Paul Irofti, Laurent Jacques, Ulugbek S. Kamilov, Srdan Kitic, Martin Kliesch, Florent Krzakala, John A. Lee, Wenzhi Liao, Tobias Lindstrøm Jensen, Andre Manoel, Hassan Mansour, Ali Mohammad-Djafari, Amirafshar Moshtaghpour, Fred Maurice Ngolè Mboula, Benoît Pairet, Marko Panic, Gabriel Peyré, Aleksandra Pizurica, Pavel Rajmic, Matthieu Roblin, Ingo Roth, Anil Kumar Sao, Pulkit Sharma, Jean-Luc Starck, Eric W. Tramel, Toon van Waterschoot, Dejan Vukobratovic, Li Wang, Benedikt Wirth, Gerhard Wunder, Hongyan Zhang
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Gabriel Peyré