Peyré, Gabriel

53 publications

ICLR 2025 Towards Understanding the Universality of Transformers for Next-Token Prediction Michael Eli Sander, Gabriel Peyré

ICML 2025 Transformative or Conservative? Conservation Laws for ResNets and Transformers Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré

ICLR 2025 Transformers Are Universal In-Context Learners Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré

AISTATS 2024 Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization Zhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin

ICML 2024 How Do Transformers Perform In-Context Autoregressive Learning ? Michael Eli Sander, Raja Giryes, Taiji Suzuki, Mathieu Blondel, Gabriel Peyré

ICML 2024 How Smooth Is Attention? Valérie Castin, Pierre Ablin, Gabriel Peyré

ICML 2024 Keep the Momentum: Conservation Laws Beyond Euclidean Gradient Flows Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré

ICLR 2024 Sparsistency for Inverse Optimal Transport Francisco Andrade, Gabriel Peyré, Clarice Poon

AISTATS 2024 Structured Transforms Across Spaces with Cost-Regularized Optimal Transport Othmane Sebbouh, Marco Cuturi, Gabriel Peyré

NeurIPS 2023 Abide by the Law and Follow the Flow: Conservation Laws for Gradient Flows Sibylle Marcotte, Remi Gribonval, Gabriel Peyré

ICML 2023 Fast, Differentiable and Sparse Top-K: A Convex Analysis Perspective Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel

AISTATS 2022 Fast and Accurate Optimization on the Orthogonal Manifold Without Retraction Pierre Ablin, Gabriel Peyré

AISTATS 2022 Faster Unbalanced Optimal Transport: Translation Invariant Sinkhorn and 1-D Frank-Wolfe Thibault Sejourne, Francois-Xavier Vialard, Gabriel Peyré

AISTATS 2022 Randomized Stochastic Gradient Descent Ascent Othmane Sebbouh, Marco Cuturi, Gabriel Peyré

AISTATS 2022 Sinkformers: Transformers with Doubly Stochastic Attention Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré

NeurIPS 2022 Do Residual Neural Networks Discretize Neural Ordinary Differential Equations? Michael Sander, Pierre Ablin, Gabriel Peyré

ICML 2022 Linear-Time Gromov Wasserstein Distances Using Low Rank Couplings and Costs Meyer Scetbon, Gabriel Peyré, Marco Cuturi

NeurIPS 2022 On Global Convergence of ResNets: From Finite to Infinite Width Using Linear Parameterization Raphaël Barboni, Gabriel Peyré, Francois-Xavier Vialard

ICML 2022 Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors Geert-Jan Huizing, Laura Cantini, Gabriel Peyré

ICML 2021 Low-Rank Sinkhorn Factorization Meyer Scetbon, Marco Cuturi, Gabriel Peyré

ICML 2021 Momentum Residual Neural Networks Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré

NeurIPS 2021 Smooth Bilevel Programming for Sparse Regularization Clarice Poon, Gabriel Peyré

NeurIPS 2021 The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation Thibault Sejourne, Francois-Xavier Vialard, Gabriel Peyré

NeurIPS 2020 Entropic Optimal Transport Between Unbalanced Gaussian Measures Has a Closed Form Hicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi

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

NeurIPS 2020 Online Sinkhorn: Optimal Transport Distances from Sample Streams Arthur Mensch, Gabriel Peyré

ICML 2020 Super-Efficiency of Automatic Differentiation for Functions Defined as a Minimum Pierre Ablin, Gabriel Peyré, Thomas Moreau

COLT 2020 Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra

FnTML 2019 Computational Optimal Transport Gabriel Peyré, Marco Cuturi

ICML 2019 Geometric Losses for Distributional Learning Arthur Mensch, Mathieu Blondel, Gabriel Peyré

AISTATS 2019 Interpolating Between Optimal Transport and MMD Using Sinkhorn Divergences Jean Feydy, Thibault Séjourné, François-Xavier Vialard, Shun-ichi Amari, Alain Trouve, Gabriel Peyré

AISTATS 2019 Model Consistency for Learning with Mirror-Stratifiable Regularizers Jalal Fadili, Guillaume Garrigos, Jérôme Malick, Gabriel Peyré

AISTATS 2019 Sample Complexity of Sinkhorn Divergences Aude Genevay, Lénaïc Chizat, Francis Bach, Marco Cuturi, Gabriel Peyré

ICML 2019 Stochastic Deep Networks Gwendoline De Bie, Gabriel Peyré, Marco Cuturi

AISTATS 2019 Support Localization and the Fisher Metric for Off-the-Grid Sparse Regularization Clarice Poon, Nicolas Keriven, Gabriel Peyré

NeurIPS 2019 Universal Invariant and Equivariant Graph Neural Networks Nicolas Keriven, Gabriel Peyré

AISTATS 2018 Learning Generative Models with Sinkhorn Divergences Aude Genevay, Gabriel Peyré, Marco Cuturi

NeurIPS 2016 A Multi-Step Inertial Forward-Backward Splitting Method for Non-Convex Optimization Jingwei Liang, Jalal Fadili, Gabriel Peyré

AISTATS 2016 Fast Dictionary Learning with a Smoothed Wasserstein Loss Antoine Rolet, Marco Cuturi, Gabriel Peyré

ICML 2016 Gromov-Wasserstein Averaging of Kernel and Distance Matrices Gabriel Peyré, Marco Cuturi, Justin Solomon

NeurIPS 2016 Sparse Support Recovery with Non-Smooth Loss Functions Kévin Degraux, Gabriel Peyré, Jalal Fadili, Laurent Jacques

NeurIPS 2016 Stochastic Optimization for Large-Scale Optimal Transport Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis Bach

NeurIPS 2015 Biologically Inspired Dynamic Textures for Probing Motion Perception Jonathan Vacher, Andrew Isaac Meso, Laurent U Perrinet, Gabriel Peyré

NeurIPS 2014 Local Linear Convergence of Forward--Backward Under Partial Smoothness Jingwei Liang, Jalal Fadili, Gabriel Peyré

ECCV 2010 Geodesic Shape Retrieval via Optimal Mass Transport Julien Rabin, Gabriel Peyré, Laurent D. Cohen

CVPR 2010 On Growth and Formlets: Sparse Multi-Scale Coding of Planar Shape Timothy D. Oleskiw, James H. Elder, Gabriel Peyré

CVPR 2009 Extraction of Tubular Structures over an Orientation Domain Mickaël Péchaud, Renaud Keriven, Gabriel Peyré

ICCV 2009 Image Compression with Anisotropic Triangulations Sébastien Bougleux, Gabriel Peyré, Laurent D. Cohen

CVPRW 2008 3D Shape Matching by Geodesic Eccentricity Adrian Ion, Nicole M. Artner, Gabriel Peyré, Salvador B. López Mármol, Walter G. Kropatsch, Laurent D. Cohen

ECCV 2008 Anisotropic Geodesics for Perceptual Grouping and Domain Meshing Sébastien Bougleux, Gabriel Peyré, Laurent D. Cohen

ECCV 2008 Non-Local Regularization of Inverse Problems Gabriel Peyré, Sébastien Bougleux, Laurent D. Cohen

CVPR 2006 Landmark-Based Geodesic Computation for Heuristically Driven Path Planning Gabriel Peyré, Laurent D. Cohen

CVPR 2005 Geodesic Computation for Adaptive Remeshing Gabriel Peyré, Laurent D. Cohen