A Low-Rank Approach to Off-The-Grid Sparse Deconvolution
Paul Catala, Vincent Duval, Gabriel Peyré
arXiv preprint, December 2017
A Characterization of the Non-Degenerate Source Condition in Super-Resolution
Vincent Duval
Hal preprint, December 2017
Minimal convex extensions and finite difference discretization of the quadratic Monge-Kantorovich problem
Jean-David Benamou, Vincent Duval
Hal preprint, October 2017
Sampling the Fourier transform along radial lines
Charles Dossal, Vincent Duval, Clarice Poon
Accepted to SIAM Journal on Numerical Analysis, 2017
Sparse Spikes Super-resolution on Thin grids II: the Continuous Basis-Pursuit
Vincent Duval, Gabriel Peyré
Inverse Problems, 33 (9) 2017
Sparse Spikes Super-resolution on Thin grids I: the LASSO
Vincent Duval, Gabriel Peyré
Inverse Problems, 33 (5) 2017
Convergence of Entropic Schemes for Optimal Transport and Gradient Flows
Guillaume Carlier, Vincent Duval, Gabriel Peyré, Bernhard Schmitzer
SIAM Journal on Mathematical Analysis, 49 (2) 2017
Geometric properties of solutions to the total variation denoising problem
Antonin Chambolle, Vincent Duval, Gabriel Peyré, Clarice Poon
Inverse Problems, 33 (1), December 2016
Support Recovery for Sparse Super-Resolution of Positive Measures
Quentin Denoyelle, Vincent Duval, Gabriel Peyré
J. of Fourier Analysis and Applications, September 2016, DOI 10.1007/s00041-016-9502-x
A Gamma-Convergence Result for the Upper Bound Limit Analysis of Plates
Jérémy Bleyer, Guillaume Carlier, Vincent Duval, Jean-Marie Mirebeau, Gabriel Peyré
ESAIM: Mathematical Modelling and Numerical Analysis, 50 (1) January 2016
The original manuscript publication is available at www.esaim-m2an.org
Exact Support Recovery for Sparse Spikes Deconvolution
Vincent Duval, Gabriel Peyré
J. of Foundations of Computational Mathematics, DOI 10.1007/s10208-014-9228-6, pp. 1-41, 2014
Non-local Methods with Shape-Adaptive Patches (NLM-SAP)
Charles-Alban Deledalle, Vincent Duval, Joseph Salmon
J. Math. Imaging Vis., 43 (2), pp. 103-120, 2012
A bias-varance approach for the non-local means
Vincent Duval, Jean-François Aujol, Yann Gousseau
SIAM Journal on Imaging Sciences, 4 (2), pp. 760-788, 2011
Mathematical Modeling of Textures: Application to Color Image Decomposition with a Projected Gradient Algorithm
Vincent Duval, Jean-François Aujol, Luminita Vese
J. Math. Imaging Vis., 37 (3), pp. 232-248, 2010
The TVL1 model: a Geometric Point of View
Vincent Duval, Jean-François Aujol, Yann Gousseau
SIAM Journal on Multiscale Model. Simul., 8 (1), pp. 154-189, 2009
Déconvolution Parcimonieuse sans Grille: une Méthode de Faible Rang
Paul Catala, Vincent Duval, Gabriel Peyré
ORASIS, 2017
Sparse Super-resolution from Laplace Measurements
Quentin Denoyelle, Vincent Duval, Gabriel Peyré
SPARS, 2017
A Low-Rank Approach to Off-The-Grid Sparse Deconvolution
Paul Catala, Vincent Duval, Gabriel Peyré
SPARS, 2017
The Non Degenerate Source Condition: Support Robustness for Discrete and Continuous Sparse Deconvolution
Vincent Duval, Gabriel Peyré
IEEE CAMSAP, 2015
Asymptotic of Sparse Support Recovery for Positive Measures
Quentin Denoyelle, Vincent Duval, Gabriel Peyré
Journal of Physics: Conference Series, 2015, Volume 657, conference 1
Discrete vs. continuous sparse regularization
Vincent Duval, Gabriel Peyré
Proceedings of iTWIST'14
Low noise regimes for l1 regularization : continuous and discrete settings
Vincent Duval, Gabriel Peyré
PAMM 14 (1), pp. 943-944, 2014
Anisotropic Non-Local Means with Spatially Adaptive Shapes
Charles-Alban Deledalle, Vincent Duval, Joseph Salmon
Scale Space and Variational Methods in Computer Vision, 2011, Springer
Projected Gradient based Color Image Decomposition
Vincent Duval, Jean-François Aujol, Luminita Vese
Scale Space and Variational Methods in Computer Vision, 2009, Springer
A comparative analysis of the TVL1 and the TV-G models
Vincent Duval
HAL preprint, December 2013. This report was written to apply to the Vincent Caselles Student Award.
Variational and non-local methods in image processing: a geometric study
Vincent Duval
Advisors: Yann Gousseau, Jean-François Aujol