Publications


of Gabriel Peyré

2024

Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization, Z. Ye, G. Peyré, D. Cremers and P. Ablin, Proc. AISTATS'23, 2024.

How do Transformers perform In-Context Autoregressive Learning?, M. E. Sander, R. Giryes, T. Suzuki, M. Blondel and G. Peyré, preprint, 2024.

Sparsistency for Inverse Optimal Transport, F. Andrade, G. Peyré and C. Poon, Proc. ICLR'23, 2024.

Structured Transforms Across Spaces with Cost-Regularized Optimal Transport, O. Sebbouh, M. Cuturi and G. Peyré, Proc. AISTATS'23, 2024.

2023

Abide by the Law and Follow the Flow: Conservation Laws for Gradient Flows, S. Marcotte, R. Gribonval and G. Peyré, Proc. NeurIPS'23, 2023.

Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective, M. Sander, J. Puigcerver, J. Djolonga, G. Peyré and M. Blondel, Proc. ICML'23, 2023.

Paired single-cell multi-omics data integration with Mowgli, G-J. Huizing, M. Deutschmann, G. Peyré and L. Cantini, Nature Communications, 2023.

Smooth over-parameterized solvers for non-smooth structured optimization, C. Poon and G. Peyré, Mathematical Programming, pp. 897-952, 2023.

Super-resolved Lasso, C. Poon and G. Peyré, preprint, 2023.

Test like you Train in Implicit Deep Learning, Z. Ramzi, P. Ablin, G. Peyré and T. Moreau, preprint, 2023.

The geometry of off-the-grid compressed sensing, C. Poon, N. Keriven and G. Peyré, Foundations of Computational Mathematics, pp. 241-327, 2023.

Unbalanced Optimal Transport, from Theory to Numerics, T. Séjourné, G. Peyré and F-X. Vialard, 2023.

Understanding the Regularity of Self-Attention with Optimal Transport, V. Castin, P. Ablin and G. Peyré, preprint, 2023.

2022

Degrees of freedom for off-the-grid sparse estimation, C. Poon and G. Peyré, Bernoulli, pp. 2095-2121, 2022.

Do Residual Neural Networks discretize Neural Ordinary Differential Equations?, M. Sander, P. Ablin and G. Peyré, Proc. NeurIPS'22, 2022.

Fast and accurate optimization on the orthogonal manifold without retraction, P. Ablin and G. Peyré, Proc. AISTATS'22, 2022.

Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe, T. Séjourné, F-X. Vialard and G. Peyré, Proc. AISTATS'22, 2022.

Global convergence of ResNets: From finite to infinite width using linear parameterization, R. Barboni, G. Peyré and F-X Vialard, Proc. NeurIPS'22, 2022.

Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs, M. Scetbon, G. Peyré and M. Cuturi, Proc. ICML'22, 2022.

Optimal Transport improves cell-cell similarity inference in single-cell omics data, G-J. Huizing, G. Peyré and L. Cantini, Bioinformatics, pp. 2169-2177, 2022.

Randomized Stochastic Gradient Descent Ascent, O. Sebbouh, M. Cuturi and G. Peyré, Proc. AISTATS'22, 2022.

Sinkformers: Transformers with Doubly Stochastic Attention, M. E. Sander, P. Ablin, M. Blondel and G. Peyré, Proc. AISTATS'22, 2022.

Unsupervised Ground Metric Learning using Wasserstein Eigenvectors, G-J. Huizing, L. Cantini and G. Peyré, Proc. ICML'22, 2022.

2021

Ground Metric Learning on Graphs, M. Heitz, N. Bonneel, D. Coeurjolly, M. Cuturi and G. Peyré, Journal of Mathematical Imaging and Vision, pp. 89-107, 2021.

Low-Rank Sinkhorn Factorization, M. Scetbon, M. Cuturi and G. Peyré, Proc. ICML'21, 2021.

Momentum Residual Neural Networks, M. E. Sander, P. Ablin, M. Blondel and G. Peyré, Proc. ICML'21, 2021.

Smooth Bilevel Programming for Sparse Regularization, C. Poon and G. Peyré, Proc. NeurIPS'21, 2021.

The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation, T. Séjourné, F-X. Vialard and G. Peyré, Proc. NeurIPS'21, 2021.

2020

Distribution-Based Invariant Deep Networks for Learning Meta-Features, G. De Bie, H. Rakotoarison, G. Peyré and M. Sebag, preprint, 2020.

Entropic Optimal Transport between (Unbalanced) Gaussian Measures has a Closed Form, H. Janati, B. Muzellec, G. Peyré and M. Cuturi, Proc. NeurIPS'20, 2020.

Faster Wasserstein Distance Estimation with the Sinkhorn Divergence, L. Chizat, P. Roussillon, F. Léger, F-X. Vialard and G. Peyré, Proc. NeurIPS'20, 2020.

Online Sinkhorn: optimal transportation distances from sample streams, A. Mensch and G. Peyré, Proc. NeurIPS'20, 2020.

Super-efficiency of automatic differentiation for functions defined as a minimum, P. Ablin, G. Peyré and T. Moreau, Proc. ICML'20, 2020.

Wasserstein Control of Mirror Langevin Monte Carlo, K. S. Zhang, G. Peyré, J. Fadili and M. Pereyra, Proc. COLT'20, 2020.

2019

Model Consistency for Learning with Mirror-Stratifiable Regularizers, J. Fadili, G. Garrigos, J. Malick and G. Peyré, Proc. AISTATS'19, 2019.

A Low-Rank Approach to Off-The-Grid Sparse Deconvolution, P. Catala, V. Duval and G. Peyré, SIAM Journal on Imaging Sciences, pp. 1464-1500, 2019.

Computational Optimal Transport, G. Peyré and M. Cuturi, Foundations and Trends in Machine Learning, pp. 1-44, 2019.

Geometric Losses for Distributional Learning, A. Mensch, M. Blondel and G. Peyré, Proc. ICML'19, 2019.

Interpolating between Optimal Transport and MMD using Sinkhorn Divergences, J. Feydy, T. Séjourné, F-X. Vialard, S. Amari, A. Trouvé and G. Peyré, Proc. AISTATS'19, 2019.

Multi-dimensional Sparse Super-resolution, C. Poon and G. Peyré, SIAM Journal on Mathematical Analysis, pp. 1-44, 2019.

Quantum Entropic Regularization of Matrix-Valued Optimal Transport, G. Peyré, L. Chizat, F-X. Vialard and J. Solomon, European Journal of Applied Mathematics, pp. 1079-1102, 2019.

Sample Complexity of Sinkhorn divergences, A. Genevay, L. Chizat, F. Bach, M. Cuturi and G. Peyré, Proc. AISTATS'19, 2019.

Sinkhorn Divergences for Unbalanced Optimal Transport, T. Séjourné, J. Feydy, F-X. Vialard, A. Trouvé and G. Peyré, preprint, 2019.

Stochastic Deep Networks, G. de Bie, G. Peyré and M. Cuturi, Proc. ICML'19, 2019.

Support Localization and the Fisher Metric for off-the-grid Sparse Regularization, C. Poon, N. Keriven and G. Peyré, Proc. AISTATS'19, 2019.

The Sliding Frank-Wolfe Algorithm and its Application to Super-Resolution Microscopy, Q. Denoyelle, V. Duval, G. Peyré and E. Soubies, Inverse Problems, pp. 014001, 2019.

Universal Invariant and Equivariant Graph Neural Networks, N. Keriven and G. Peyré, Proc. NeurIPS'19, 2019.

2018

Adaptive sup-norm estimation of the {Wigner} function in noisy quantum homodyne tomography, K. Lounici, K. Meziani and G. Peyré, The Annals of Statistics, pp. 1318-1351, 2018.

An Interpolating Distance between Optimal Transport and {Fisher-Rao}, L. Chizat, B. Schmitzer, G. Peyré and F-X. Vialard, Foundations of Computational Mathematics, pp. 1-44, 2018.

Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures, J. Vacher, A. I. Meso, G. Peyré and L. Perrinet, Neural Computation, pp. 3355-3392, 2018.

Learning Generative Models with Sinkhorn Divergences, A. Genevay, G. Peyré and M. Cuturi, Proc. AISTATS'18, pp. 1608-1617, 2018.

Local Linear Convergence Analysis of Primal-Dual Splitting Methods, J. Liang, J. Fadili and G. Peyré, Optimization, pp. 821-853, 2018.

Scaling Algorithms for Unbalanced Transport Problems, L. Chizat, G. Peyré , B. Schmitzer and F-X. Vialard, Mathematics of Computation, pp. 2563-2609, 2018.

Semidual Regularized Optimal Transport, M. Cuturi and G. Peyré, SIAM Review, pp. 941-965, 2018.

Sensitivity Analysis for Mirror-Stratifiable Convex Functions, J. Fadili, J. Malick and G. Peyré, SIAM Journal on Optimization, pp. 2975-3000, 2018.

Unbalanced Optimal Transport: Geometry and Kantorovich Formulation, L. Chizat, G. Peyré , B. Schmitzer and F-X. Vialard, Journal of Functional Analysis, pp. 3090-3123, 2018.

Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning, M. Schmitz, M. Heitz, N. Bonneel, F. M. Ngole Mboula, D. Coeurjolly, M. Cuturi, G. Peyré and J-L. Starck, SIAM Journal on Imaging Sciences, pp. 643-678, 2018.

2017

Activity Identification and Local Linear Convergence of Forward--Backward-type methods, J. Liang, J. Fadili and G. Peyré, SIAM Journal on Optimization, pp. 408-437, 2017.

Claude Shannon et la compression des donn{\'e}es, G. Peyré, pp. 230-230, 2017.

Convergence of Entropic Schemes for Optimal Transport and Gradient Flows, G. Carlier, V. Duval, G. Peyré and B. Schmitzer, SIAM Journal on Mathematical Analysis, pp. 1385-1418, 2017.

Geometric properties of solutions to the total variation denoising problem, A. Chambolle, V. Duval, G. Peyré and C. Poon, Inverse Problems, pp. 015002, 2017.

Local Convergence Properties of Douglas--Rachford and Alternating Direction Method of Multipliers, J. Liang, J. Fadili and G. Peyré, Journal of Optimization Theory and Applications, pp. 874-913, 2017.

Model Consistency of Partly Smooth Regularizers, S. Vaiter, G. Peyré and J. Fadili, IEEE Transactions on Information Theory, pp. 1725-1737, 2017.

Optimal Transport for Diffeomorphic Registration, Jean Feydy, Benjamin Charlier, Francois-Xavier Vialard and Gabriel Peyré, Proc. MICCAI'17, pp. 291-299, 2017.

Sparse Spikes Super-resolution on Thin Grids {II}: the Continuous Basis Pursuit, V. Duval and G. Peyré, Inverse Problems, pp. 095008, 2017.

Sparse Spikes Super-resolution on Thin Grids {I}: the LASSO, V. Duval and G. Peyré, Inverse Problems, pp. 055008, 2017.

Support Recovery for Sparse Super-Resolution of Positive Measures, Q. Denoyelle, V. Duval and G. Peyré, Journal of Fourier Analysis and Applications, pp. 1153-1194, 2017.

The Degrees of Freedom of Partly Smooth Regularizers, S. Vaiter, C. Deledalle, G. Peyré, J. Fadili and C. Dossal, Annals of the Institute of Statistical Mathematics, pp. 791-832, 2017.

2016

A Gamma-Convergence Result for the Upper Bound Limit Analysis of Plates, J. Bleyer, G. Carlier, V. Duval, J-M. Mirebeau and G. Peyré, ESAIM: Mathematical Modelling and Numerical Analysis, pp. 215-235, 2016.

A Multi-step Inertial Forward-Backward Splitting Method for Non-convex Optimization, J. Liang, J. Fadili and G. Peyré, Proc. NIPS'16, pp. 4035-4043, 2016.

A Smoothed Dual Approach for Variational Wasserstein Problems, M. Cuturi and G. Peyré, SIAM Journal on Imaging Sciences, pp. 320-343, 2016.

An automated workflow for the anatomo-functional mapping of the barrel cortex, L. Perronnet, M.E. Vilarchao, G. Hucher, D.E. Shulz, G. Peyré and I. Ferezou, Journal of Neuroscience Methods, pp. 145-154, 2016.

Convergence Rates with Inexact Non-expansive Operators, J. Liang, J. Fadili and G. Peyré, Mathematical Programming, pp. 403-434, 2016.

Entropic Metric Alignment for Correspondence Problems, J. Solomon, G. Peyré, V. Kim and S. Sra, ACM Transactions on Graphics (Proc. SIGGRAPH 2016), pp. 72:1-72:13, 2016.

Fast Dictionary Learning with a Smoothed Wasserstein Loss, A. Rolet, M. Cuturi and G. Peyré, Proc. AISTATS'16, pp. 630-638, 2016.

Finsler Steepest Descent with Applications to Piecewise-regular Curve Evolution, G. Charpiat, G. Nardi, G. Peyré and F-X. Vialard, Interfaces and Free Boundaries, pp. 1-44, 2016.

Geodesics on Shape Spaces with Bounded Variation and Sobolev Metrics, G. Nardi, G. Peyré and F-X. Vialard, SIAM Journal on Imaging Sciences, pp. 238-274, 2016.

Gromov-Wasserstein Averaging of Kernel and Distance Matrices, G. Peyré, M. Cuturi and J. Solomon, Proc. ICML'16, pp. 2664-2672, 2016.

Parcimonie, problemes inverse et {\'e}chantillonnage compress{\'e}, G. Peyré, pp. 40-49, 2016.

Sparse Support Recovery with Non-smooth Loss Functions, K. Degraux, G. Peyré, J. Fadili and L. Jacques, Proc. NIPS'16, pp. 4269-4277, 2016.

Spatially Structured Sparse Morphological Component Separation for Voltage-Sensitive Dye Optical Imaging, H. Raguet, C. Monier, L. Foubert, I. Ferezou, Y. Fregnac and G. Peyré, Journal of Neuroscience Methods, pp. 76-96, 2016.

Stochastic Optimization for Large-scale Optimal Transport, A. Genevay, M. Cuturi, G. Peyré and F. Bach, Proc. NIPS'16, pp. 3432-3440, 2016.

Wasserstein Barycentric Coordinates: Histogram Regression Using Optimal Transport, N. Bonneel, G. Peyré and M. Cuturi, ACM Transactions on Graphics (Proc. SIGGRAPH 2016), pp. 71:1-71:10, 2016.

Wasserstein Loss for Image Synthesis and Restoration, G. Tartavel, G. Peyré and Y. Gousseau, SIAM Journal on Imaging Sciences, pp. 1726-1755, 2016.

2015

Activity Identification and Local Linear Convergence of Douglas-Rachford/ADMM under Partial Smoothness, J. Liang, J. Fadili, G. Peyré and R. Luke, Proc. SSVM'15, pp. 642-653, 2015.

Biologically Inspired Dynamic Textures for Probing Motion Perception, J. Vacher, A. I. Meso, G. Peyré and L. Perrinet, Proc. NIPS'15, pp. 1909-1917, 2015.

Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains, J. Solomon, F. de Goes, G. Peyré, M. Cuturi, A. Butscher, A. Nguyen, T. Du and L. Guibas, ACM Transactions on Graphics (Proc. SIGGRAPH 2015), pp. 66:1-66:11, 2015.

Entropic Approximation of {Wasserstein} Gradient Flows, G. Peyré, SIAM Journal on Imaging Sciences, pp. 2323-2351, 2015.

Exact Support Recovery for Sparse Spikes Deconvolution, V. Duval and G. Peyré, Foundations of Computational Mathematics, pp. 1315-1355, 2015.

Fast Optimal Transport Averaging of Neuroimaging Data, A. Gramfort, G. Peyré and M. Cuturi, Proc. IPMI'15, pp. 261-272, 2015.

Iterative {Bregman} Projections for Regularized Transportation Problems, J-D. Benamou, G. Carlier, M. Cuturi, L. Nenna and G. Peyré, SIAM Journal on Scientific Computing, pp. A1111-A1138, 2015.

Low Complexity Regularization of Linear Inverse Problems, S. Vaiter, G. Peyré and J. Fadili, pp. 103-153, 2015.

Model Selection with Low Complexity Priors, S. Vaiter, M. Golbabaee, J. Fadili and G. Peyré, Information and Inference, pp. 230-287, 2015.

Sliced and Radon Wasserstein Barycenters of Measures, N. Bonneel, J. Rabin, G. Peyré and H. Pfister, Journal of Mathematical Imaging and Vision, pp. 22-45, 2015.

The Non Degenerate Source Condition: Support Robustness for Discrete and Continuous Sparse Deconvolution, V. Duval and G. Peyré, Proc. IEEE CAMSAP'15, pp. 49-52, 2015.

Variational Texture Synthesis with Sparsity and Spectrum Constraints, G. Tartavel, Y. Gousseau and G. Peyré, Journal of Mathematical Imaging and Vision, pp. 124-144, 2015.

2014

Iteration-Complexity of a Generalized Forward Backward Splitting Algorithm, J. Liang, J. Fadili and G. Peyré, Proc. ICASSP'14, 2014.

Local Linear Convergence of Forward-Backward under Partial Smoothness, J. Liang, J. Fadili and G. Peyré, Proc. NIPS'14, pp. 1970-1978, 2014.

On the convergence rates of proximal splitting algorithms, J. Liang, J. Fadili and G. Peyré, Proc. ICIP'14, pp. 4146-4150, 2014.

Optimal Transport with Proximal Splitting, N. Papadakis, G. Peyré and E. Oudet, SIAM Journal on Imaging Sciences, pp. 212-238, 2014.

Regularized Discrete Optimal Transport, S. Ferradans, N. Papadakis, G. Peyré and J-F. Aujol, SIAM Journal on Imaging Sciences, pp. 1853-1882, 2014.

Stein Unbiased GrAdient estimator of the Risk (SUGAR) for multiple parameter selection, C. Deledalle, S. Vaiter, G. Peyré and J. Fadili, SIAM Journal on Imaging Sciences, pp. 2448-2487, 2014.

Synthesizing and Mixing Stationary Gaussian Texture Models, G-S. Xia, S. Ferradans, G. Peyré and J-F. Aujol, SIAM Journal on Imaging Sciences, pp. 476-508, 2014.

2013

A Generalized Forward-Backward Splitting, H. Raguet, J. Fadili and G. Peyré, SIAM Journal on Imaging Sciences, pp. 1199-1226, 2013.

Adaptive estimation of the density matrix in quantum homodyne tomography with noisy data, P. Alquier, K. Meziani and G. Peyré, Inverse Problems, pp. 075017, 2013.

Constrained Sparse Texture Synthesis, G. Tartavel, Y. Gousseau and G. Peyré, Proc. SSVM'13, pp. 186-197, 2013.

Local Behavior of Sparse Analysis Regularization: Applications to Risk Estimation, S. Vaiter, C. Deledalle, G. Peyré, J. Fadili and C. Dossal, Applied and Computational Harmonic Analysis, pp. 433-451, 2013.

On Growth and Formlets: Sparse Multi-Scale Coding of Planar Shape, J. Elder, T. Oleskiw, A. Yakubovich and G. Peyré, Image and Vision Computing, pp. 1-13, 2013.

Regularized Discrete Optimal Transport, S. Ferradans, N. Papadakis, G. Peyré and J-F. Aujol, Proc. SSVM'13, pp. 428-439, 2013.

Robust Polyhedral Regularization, S. Vaiter , G. Peyré and J. Fadili, Proc. Sampta'13, pp. 156-159, 2013.

Robust Sparse Analysis Regularization, S. Vaiter, G. Peyré, C. Dossal and J. Fadili, IEEE Transactions on Information Theory, pp. 2001-2016, 2013.

Stable Recovery with Analysis Decomposable Priors, J. Fadili, G. Peyré, S. Vaiter, C. Deledalle and J. Salmon, Proc. Sampta'13, pp. 113-116, 2013.

Static and Dynamic Texture Mixing Using Optimal Transport, S. Ferradans, G-S. Xia , G. Peyré and J-F. Aujol, Proc. SSVM'13, pp. 137-148, 2013.

Stein COnsistent Risk Estimator (SCORE) for hard thresholding, C. Deledalle, G. Peyré and J. Fadili, Proc. SPARS'13, 2013.

The degrees of freedom of penalized l1 minimization, C. Dossal, M. Kachour, J. Fadili, G. Peyré and C. Chesneau, Statistica Sinica, pp. 809-828, 2013.

2012

Compact Representations of Stationary Dynamic Textures, G-S. Xia , S. Ferradans, G. Peyré and J-F. Aujol, Proc. ICIP'12, pp. 2993-2996, 2012.

Degrees of Freedom of the Group Lasso, S. Vaiter, C. Deledalle, G. Peyré, J. Fadili and C. Dossal, Proc. ICML'12 Workshops, 2012.

Le traitement num{\'e}rique des images, G. Peyré, pp. 593-694, 2012.

Nonlocal Active Contours, M. Jung, G. Peyré and L. D. Cohen, SIAM Journal on Imaging Sciences, pp. 1022-1054, 2012.

Proximal Splitting Derivatives for Risk Estimation, C. Deledalle, S. Vaiter, G. Peyré, J. Fadili and C. Dossal, Proc. NCMIP'12, 2012.

Risk estimation for matrix recovery with spectral regularization, C. Deledalle, S. Vaiter, G. Peyré, J. Fadili and C. Dossal, Proc. ICML'12 Workshops, 2012.

Sharp Support Recovery from Noisy Random Measurements by L1 minimization, C. Dossal, M.L. Chabanol, G. Peyré and J. Fadili, Applied and Computational Harmonic Analysis, pp. 24-43, 2012.

Unbiased Risk Estimation for Sparse Analysis Regularization, C. Deledalle, S. Vaiter, G. Peyré, J. Fadili and C. Dossal, Proc. ICIP'12, pp. 3053-3056, 2012.

Wasserstein Active Contours, G. Peyré, J. Fadili and J. Rabin, Proc. ICIP'12, pp. 2541-2544, 2012.

2011

A Panorama on Multiscale Geometric Representations, Intertwining Spatial, Directional and Frequency Selectivity, L. Jacques, L. Duval, C. Chaux and G. Peyré, Signal Processing, pp. 2699-273, 2011.

A Projection Approach to the Numerical Analysis of Limit Load Problems, G. Carlier, M. Comte, I. Ionescu and G. Peyré, Mathematical Models and Methods in Applied Sciences, pp. 1291-1316, 2011.

A Review of Adaptive Image Representations, G. Peyré, IEEE Journal of Selected Topics in Signal Processing, pp. 896-911, 2011.

Adaptive Structured Block Sparsity Via Dyadic Partitioning, G. Peyré, J. Fadili and C. Chesneau, Proc. EUSIPCO 2011, pp. 1455-1459, 2011.

Apprentissage d'a priori analyse, G. Peyré and J. Fadili, Gretsi'11, 2011.

Compressive Wave Computation, L. Demanet and G. Peyré, Foundations of Computational Mathematics, pp. 257-303, 2011.

Dissipative Wave Model Fitting Using Localized Sources, N. Schmidt, G. Peyré and Y. Fregnac, Proc. Waves 2011, pp. 473-476, 2011.

Group Sparsity with Overlapping Partition Functions, G. Peyré and J. Fadili, Proc. EUSIPCO 2011, pp. 303-307, 2011.

Learning Analysis Sparsity Priors, G. Peyré and J. Fadili, Proc. of Sampta'11, 2011.

Locally Parallel Texture Modeling, P. Maurel, J-F. Aujol and G. Peyré, SIAM Journal on Imaging Sciences, pp. 413-447, 2011.

Matching 2D and 3D Articulated Shapes Using the Eccentricity Transform, A. Ion, N. M. Artner, G. Peyré, W. G. Kropatsch and L. D. Cohen, Computer Vision and Image Understanding, pp. 817-834, 2011.

Non-local Active Contours, M. Jung, G. Peyré and L. D. Cohen, LNCS, Proc. SSVM'11, pp. 255-266, 2011.

Non-local Regularization of Inverse Problems, G. Peyré, S. Bougleux and L. D. Cohen, Inverse Problems and Imaging, pp. 511-530, 2011.

Non-local Segmentation and Inpainting, M. Jung, G. Peyré and L. D. Cohen, Proc. ICIP'11, 2011.

Parcimonie Adaptative Structuree par Blocs Dyadiques, G. Peyré, J. Fadili and C. Chesneau, Gretsi'11, 2011.

Regularisation de Wasserstein et Application au Transfert de Couleur, J. Rabin and G. Peyré, Gretsi'11, 2011.

Synthese de textures par transport optimal, G. Peyré and J. Rabin, Gretsi'11, 2011.

Texture Segmentation via Non-local Non-parametric Active Contours, M. Jung, G. Peyré and L. D. Cohen, Proc. EMMCVPR 2011, pp. 74-88, 2011.

The Numerical Tours of Signal Processing - Advanced Computational Signal and Image Processing, G. Peyré, IEEE Computing in Science and Engineering, pp. 94-97, 2011.

The degrees of freedom of the Lasso in underdetermined linear regression models, M. Kachour, C. Dossal, J. Fadili, G. Peyré and C. Chesneau, Proc. SPARS 2011, 2011.

Total Variation Projection with First Order Schemes, J. Fadili and G. Peyré, IEEE Transactions on Image Processing, pp. 657-669, 2011.

Un exploration numerique du traitement des signaux, des images et des surfaces, G. Peyré, pp. 41-64, 2011.

Wasserstein Regularization of Imaging Problem, J. Rabin and G. Peyré, Proc. ICIP'11, pp. 1541-1544, 2011.

Wassertein Barycenter and its Applications to Texture Mixing, J. Rabin, G. Peyré, J. Delon and M. Bernot, LNCS, Proc. SSVM'11, pp. 435-446, 2011.

2010

A Numerical Exploration of Compressed Sampling Recovery, C. Dossal, G. Peyré and J. Fadili, Linear Algebra and Applications, pp. 1663-1679, 2010.

Best Basis Compressed Sensing, G. Peyré, IEEE Transaction on Signal Processing, pp. 2613-2622, 2010.

Derivatives with Respect to Metrics and Applications: Subgradient Marching Algorithm, F. Benmansour, G. Carlier, G. Peyré and F. Santambrogio, Numerische Mathematik, pp. 357-381, 2010.

Geodesic Methods in Computer Vision and Graphics, G. Peyré, M. Pechaud, R. Keriven and L.D. Cohen, Foundations and Trends in Computer Graphics and Vision, pp. 197-397, 2010.

Geodesic Shapes and Surfaces Retrieval via Optimal Mass Transport, J. Rabin, G. Peyré and L. D. Cohen, Proc. of ECCV'10, pp. 771-784, 2010.

Learning the Morphological Diversity, G. Peyré, J. Fadili and J-L. Starck, SIAM Journal on Imaging Sciences, pp. 646-669, 2010.

On Growth and Formlets: Sparse Multi-Scale Coding of Planar Shape, T. Oleskiw, G. Peyré and J. Elder, Proc. of CVPR'10, pp. 459-466, 2010.

Separation of Traveling Waves in Cortical Networks Using Optical Imaging, N. Schmidt, G. Peyré, Y. Fregnac and P. E. Roland, Proc. of ISBI'10, pp. 868-871, 2010.

Texture Synthesis with Grouplets, G. Peyré, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 733-746, 2010.

2009

A Numerical Exploration of Compressed Sampling Recovery, C. Dossal, G. Peyré and J. Fadili, Proc. of SPARS'09, 2009.

Algorithmes de premier ordre pour la projection sur une contrainte de variation totale, G. Peyré and J. Fadili, Gretsi'09, 2009.

Approximation of Maximal Cheeger Sets by Projection, G. Carlier, M. Comte and G. Peyré, ESAIM: Mathematical Modelling and Numerical Analysis, pp. 131-150, 2009.

Best Basis Denoising with Non-stationary Wavelet Packets, N. Ouarti and G. Peyré, Proc. of ICIP'09, pp. 3825-3828, 2009.

Challenging Restricted Isometry Constants with Greedy Pursuit, C. Dossal, G. Peyré and J. Fadili, Proc. of ITW'09, pp. 475-479, 2009.

Compression d'images par triangulations geodesiques anisotropes, S. Bougleux, G. Peyré and L. D. Cohen, Gretsi'09, 2009.

Dynamic Texture Synthesis with Grouplets, G. Peyré, Proc. of MAPMO, pp. 103-117, 2009.

Extraction de textures localement paralleles par un espace de Hilbert adapte, P. Maurel, J-F. Aujol and G. Peyré, Gretsi'09, 2009.

Extraction of Tubular Structures over an Orientation Domain, M. Pechaud, G. Peyré and R. Keriven, Proc. of CVPR'09, pp. 336-342, 2009.

Image Compression with Anisotropic Geodesic Triangulations, S. Bougleux, G. Peyré and L. D. Cohen, Proc. of ICCV'09, pp. 2343-2348, 2009.

Locally Parallel Textures Modeling with Adapted Hilbert Spaces, P. Maurel, J-F. Aujol and G. Peyré, Proc. of EMMCVPR'09, pp. 429-442, 2009.

Manifold models for signals and images, G. Peyré, Computer Vision and Image Understanding, pp. 249-260, 2009.

Numerical Approximation of Continuous Traffic Congestion Equilibria, F. Benmansour, G. Carlier, G. Peyré and F. Santambrogio, Networks and Eterogeneous Media, pp. 605-623, 2009.

Sparse Modeling of Textures, G. Peyré, Journal of Mathematical Imaging and Vision, pp. 17-31, 2009.

Total Variation Projection with First Order Schemes, J. Fadili and G. Peyré, Proc. of ICIP'09, pp. 1325-1328, 2009.

Une exploration numerique des performances de l'echantillonage compresse, C. Dossal, G. Peyré and J. Fadili, Gretsi'09, 2009.

2008

3D shape matching by geodesic eccentricity, A. Ion, N. M. Artner, G. Peyré, S. B. L. Marmol, W. G. Kropatsch and L. D. Cohen, Proc. Computer Vision and Pattern Recognition Workshops, pp. 1-8, 2008.

Anisotropic Geodesics for Perceptual Grouping and Domain Meshing, S. Bougleux, G. Peyré and L. D. Cohen, Proc. of ECCV'08, pp. 129-142, 2008.

Geodesic Methods for Shape and Surface Processing, G. Peyré and L. D. Cohen, pp. 29-56, 2008.

Heuristically Driven Front Propagation for Fast Geodesic Extraction, G. Peyré and L. D. Cohen, International Journal for Computational Vision and Biomechanics, pp. 55-67, 2008.

Image Processing with Non-local Spectral Bases, G. Peyré, SIAM Multiscale Modeling and Simulation, pp. 703-730, 2008.

Non-local Regularization of Inverse Problems, G. Peyré and S. Bougleux and L. D. Cohen, Proc. of ECCV'08, pp. 57-68, 2008.

Orthogonal Bandlet Bases for Geometric Images Approximation, S. Mallat and G. Peyré, Communications on Pure and Applied Mathematics, pp. 1173-1212, 2008.

2007

A review of Bandlet methods for geometrical image representation, S. Mallat and G. Peyré, Numerical Algorithms, pp. 205-234, 2007.

Apprentissage de dictionnaires parcimonieux adaptes pour la separation d'images, G. Peyré, J. Fadili and J-L. Starck, Gretsi'07, 2007.

Best Basis Compressed Sensing, G. Peyré, Proc. of SSVM'07, pp. 80-91, 2007.

Crit{\`e}re d'identifiabilite pour la minimisation L1, C. Dossal and G. Peyré, Gretsi'07, 2007.

Estimation geometrique d'images et bases de bandelettes orthogonales, E. LePennec, C. Dossal and G. Peyré, Gretsi'07, 2007.

Geometric Estimation with Orthogonal Bandlet Bases, G. Peyré, E. LePennec, C. Dossal and S. Mallat, Proc. of SPIE Wavelet XII, pp. 67010M.1-67010M.10, 2007.

Learning Adapted Dictionaries for Geometry and Texture Separation, G. Peyré, J. Fadili and J-L. Starck, Proc. of SPIE Wavelet XII, pp. 67011T, 2007.

Non-negative Sparse Modeling of Textures, G. Peyré, Proc. of SSVM'07, pp. 628-639, 2007.

Shape Matching Using the Geodesic Eccentricity Transform - A Study, A. Ion, G. Peyré, Y. Haxhimusa, S. Peltier, W. G. Kropatsch and L. D. Cohen, Proc. of OAGM'07, 2007.

Texture Synthesis and Modification with a Patch-Valued Wavelet Transform, G. Peyré, Proc. of SSVM'07, pp. 640-651, 2007.

2006

Geodesic Remeshing Using Front Propagation, G. Peyré and L. D. Cohen, International Journal of Computer Vision, pp. 145-156, 2006.

Landmark-Based Geodesic Computation for Heuristically Driven Path Planning, G. Peyré and L. D. Cohen, Proc. of CVPR'06, pp. 2229-2236, 2006.

Random Sensing of Geometric Images, G. Peyré, Neurocomp'06, pp. 91-94, 2006.

Traitement geometrique des images par bandelettes, S. Mallat and G. Peyré, 2006.

2005

Discrete bandelets with geometric orthogonal filters, G. Peyré and S. Mallat, Proc. of ICIP'05, pp. 65-68, 2005.

Geodesic Computation for Adaptive Remeshing, G. Peyré and L. D. Cohen, Proc. of CVPR'05 (video), pp. 1193, 2005.

Geodesic Computations for Fast and Accurate Surface Remeshing and Parameterization, G. Peyré and L. D. Cohen, pp. 157-171, 2005.

Heuristically Driven Front Propagation for Geodesic Paths Extraction, G. Peyré and L. D. Cohen, Proc. of VLSM'05, pp. 173-185, 2005.

Surface compression with geometric bandelets, G. Peyré and S. Mallat, ACM Transactions on Graphics (Proc. SIGGRAPH 2005), pp. 601-608, 2005.

2004

L'algebre discr{\`e}te de la transform{\'e}e de Fourier, G. Peyré, 2004.

Objectif Agr{\'e}gation, 2e {\'e}dition, V. Beck, J. Malick and G. Peyré, 2004.

Remaillage geodesique par propagation de fronts, G. Peyré and L. D. Cohen, RFIA'04, 2004.

Surface Segmentation Using Geodesic Centroidal Tesselation, G. Peyré and L. D. Cohen, Proc. of 3DPVT'04, pp. 995-1002, 2004.

2003

Geodesic re-meshing and parameterization using front propagation, G. Peyré and L. D. Cohen, Proc. of VLSM'03, pp. 33-40, 2003.