| 2025 | ICLR | Transformers are Universal In-context Learners. | Takashi Furuya, Maarten V. de Hoop, Gabriel Peyr |
| 2025 | ICLR | Towards Understanding the Universality of Transformers for Next-Token Prediction. | Michael Eli Sander, Gabriel Peyr |
| 2025 | ICML | Transformative or Conservative? Conservation laws for ResNets and Transformers. | Sibylle Marcotte, Rmi Gribonval, Gabriel Peyr |
| 2024 | AISTATS | Structured Transforms Across Spaces with Cost-Regularized Optimal Transport. | Othmane Sebbouh, Marco Cuturi, Gabriel Peyr |
| 2024 | AISTATS | Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization. | Zhenzhang Ye, Gabriel Peyr, Daniel Cremers, Pierre Ablin |
| 2024 | ICLR | Sparsistency for inverse optimal transport. | Francisco Andrade, Gabriel Peyr, Clarice Poon |
| 2024 | ICML | How Smooth Is Attention? | Valrie Castin, Pierre Ablin, Gabriel Peyr |
| 2024 | ICML | Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows. | Sibylle Marcotte, Rmi Gribonval, Gabriel Peyr |
| 2024 | ICML | How do Transformers Perform In-Context Autoregressive Learning ? | Michael Eli Sander, Raja Giryes, Taiji Suzuki, Mathieu Blondel, Gabriel Peyr |
| 2023 | ICML | Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. | Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyr, Mathieu Blondel |
| 2022 | AISTATS | Fast and accurate optimization on the orthogonal manifold without retraction. | Pierre Ablin, Gabriel Peyr |
| 2022 | AISTATS | Sinkformers: Transformers with Doubly Stochastic Attention. | Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyr |
| 2022 | AISTATS | Randomized Stochastic Gradient Descent Ascent. | Othmane Sebbouh, Marco Cuturi, Gabriel Peyr |
| 2022 | AISTATS | Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe. | Thibault Sjourn, Franois-Xavier Vialard, Gabriel Peyr |
| 2022 | ICML | Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors. | Geert-Jan Huizing, Laura Cantini, Gabriel Peyr |
| 2022 | ICML | Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. | Meyer Scetbon, Gabriel Peyr, Marco Cuturi |
| 2021 | ICML | Momentum Residual Neural Networks. | Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyr |
| 2021 | ICML | Low-Rank Sinkhorn Factorization. | Meyer Scetbon, Marco Cuturi, Gabriel Peyr |
| 2020 | COLT | Wasserstein Control of Mirror Langevin Monte Carlo. | Kelvin Shuangjian Zhang, Gabriel Peyr, Jalal Fadili, Marcelo Pereyra |
| 2020 | ICML | Super-efficiency of automatic differentiation for functions defined as a minimum. | Pierre Ablin, Gabriel Peyr, Thomas Moreau |
| 2019 | AISTATS | Model Consistency for Learning with Mirror-Stratifiable Regularizers. | Jalal Fadili, Guillaume Garrigos, Jrme Malick, Gabriel Peyr |
| 2019 | AISTATS | Interpolating between Optimal Transport and MMD using Sinkhorn Divergences. | Jean Feydy, Thibault Sjourn, Franois-Xavier Vialard, Shun-ichi Amari, Alain Trouv, Gabriel Peyr |
| 2019 | AISTATS | Sample Complexity of Sinkhorn Divergences. | Aude Genevay, Lnac Chizat, Francis R. Bach, Marco Cuturi, Gabriel Peyr |
| 2019 | AISTATS | Support Localization and the Fisher Metric for off-the-grid Sparse Regularization. | Clarice Poon, Nicolas Keriven, Gabriel Peyr |
| 2019 | ICML | Stochastic Deep Networks. | Gwendoline de Bie, Gabriel Peyr, Marco Cuturi |
| 2019 | ICML | Geometric Losses for Distributional Learning. | Arthur Mensch, Mathieu Blondel, Gabriel Peyr |
| 2018 | AISTATS | Learning Generative Models with Sinkhorn Divergences. | Aude Genevay, Gabriel Peyr, Marco Cuturi |
| 2017 | MICCAI | Optimal Transport for Diffeomorphic Registration. | Jean Feydy, Benjamin Charlier, Franois-Xavier Vialard, Gabriel Peyr |
| 2016 | AISTATS | Fast Dictionary Learning with a Smoothed Wasserstein Loss. | Antoine Rolet, Marco Cuturi, Gabriel Peyr |
| 2016 | ICML | Gromov-Wasserstein Averaging of Kernel and Distance Matrices. | Gabriel Peyr, Marco Cuturi, Justin Solomon |
| 2014 | ICIP | On the convergence rates of proximal splitting algorithms. | Jingwei Liang, Mohamed-Jalal Fadili, Gabriel Peyr |
| 2012 | ICIP | Unbiased risk estimation for sparse analysis regularization. | Charles-Alban Deledalle, Samuel Vaiter, Gabriel Peyr, Jalal Fadili, Charles Dossal |
| 2012 | ICIP | Wasserstein active contours. | Gabriel Peyr, Jalal Fadili, Julien Rabin |
| 2012 | ICIP | Compact representations of stationary dynamic textures. | Gui-Song Xia, Sira Ferradans, Gabriel Peyr, Jean-Franois Aujol |
| 2011 | ICIP | Non-local segmentation and inpaiting. | Miyoun Jung, Gabriel Peyr, Laurent D. Cohen |
| 2011 | ICIP | Wasserstein regularization of imaging problem. | Julien Rabin, Gabriel Peyr |
| 2010 | CVPR | On growth and formlets: Sparse multi-scale coding of planar shape. | Timothy D. Oleskiw, James H. Elder, Gabriel Peyr |
| 2010 | ECCV | Geodesic Shape Retrieval via Optimal Mass Transport. | Julien Rabin, Gabriel Peyr, Laurent D. Cohen |
| 2009 | CVPR | Extraction of tubular structures over an orientation domain. | Mickal Pchaud, Renaud Keriven, Gabriel Peyr |
| 2009 | ICCV | Image compression with anisotropic triangulations. | Sbastien Bougleux, Gabriel Peyr, Laurent D. Cohen |
| 2009 | ICIP | Total variation projection with first order schemes. | Mohamed-Jalal Fadili, Gabriel Peyr |
| 2009 | ICIP | Best basis denoising with non-stationary wavelet packets. | Nizar Ouarti, Gabriel Peyr |
| 2008 | CVPR | 3D shape matching by geodesic eccentricity. | Adrian Ion, Nicole M. Artner, Gabriel Peyr, Salvador B. Lpez Mrmol, Walter G. Kropatsch, Laurent D. Cohen |
| 2008 | ECCV | Anisotropic Geodesics for Perceptual Grouping and Domain Meshing. | Sbastien Bougleux, Gabriel Peyr, Laurent D. Cohen |
| 2008 | ECCV | Non-local Regularization of Inverse Problems. | Gabriel Peyr, Sbastien Bougleux, Laurent D. Cohen |
| 2006 | CVPR | Landmark-Based Geodesic Computation for Heuristically Driven Path Planning. | Gabriel Peyr, Laurent D. Cohen |
| 2005 | CVPR | Geodesic Computation for Adaptive Remeshing. | Gabriel Peyr, Laurent D. Cohen |
| 2005 | ICIP | Discrete bandelets with geometric orthogonal filters. | Gabriel Peyr, Stphane Mallat |