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Marcelo Pereyra
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Year
Efficient bayesian computation by proximal markov chain monte carlo: when langevin meets moreau
A Durmus, E Moulines, M Pereyra
SIAM Journal on Imaging Sciences 11 (1), 473-506, 2018
2262018
Bayesian computation: a summary of the current state, and samples backwards and forwards
PJ Green, K Łatuszyński, M Pereyra, CP Robert
Statistics and Computing 25, 835-862, 2015
2192015
Proximal markov chain monte carlo algorithms
M Pereyra
Statistics and Computing 26, 745-760, 2016
2032016
A survey of stochastic simulation and optimization methods in signal processing
M Pereyra, P Schniter, E Chouzenoux, JC Pesquet, JY Tourneret, ...
IEEE Journal of Selected Topics in Signal Processing 10 (2), 224-241, 2015
1682015
Estimating the granularity coefficient of a Potts-Markov random field within a Markov chain Monte Carlo algorithm
M Pereyra, N Dobigeon, H Batatia, JY Tourneret
IEEE Transactions on Image Processing 22 (6), 2385-2397, 2013
1102013
Bayesian imaging using plug & play priors: when langevin meets tweedie
R Laumont, VD Bortoli, A Almansa, J Delon, A Durmus, M Pereyra
SIAM Journal on Imaging Sciences 15 (2), 701-737, 2022
892022
Segmentation of skin lesions in 2-D and 3-D ultrasound images using a spatially coherent generalized Rayleigh mixture model
M Pereyra, N Dobigeon, H Batatia, JY Tourneret
IEEE transactions on medical imaging 31 (8), 1509-1520, 2012
872012
Maximum-a-posteriori estimation with Bayesian confidence regions
M Pereyra
SIAM Journal on Imaging Sciences 10 (1), 285-302, 2017
802017
Maximum-a-posteriori estimation with unknown regularisation parameters
M Pereyra, JM Bioucas-Dias, MAT Figueiredo
2015 23rd European Signal Processing Conference (EUSIPCO), 230-234, 2015
782015
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo
N Brosse, A Durmus, É Moulines, M Pereyra
Conference on learning theory, 319-342, 2017
772017
Uncertainty quantification for radio interferometric imaging–I. Proximal MCMC methods
X Cai, M Pereyra, JD McEwen
Monthly Notices of the Royal Astronomical Society 480 (3), 4154-4169, 2018
722018
Scalable Bayesian uncertainty quantification in imaging inverse problems via convex optimization
A Repetti, M Pereyra, Y Wiaux
SIAM Journal on Imaging Sciences 12 (1), 87-118, 2019
712019
Wasserstein control of mirror langevin monte carlo
KS Zhang, G Peyré, J Fadili, M Pereyra
Conference on learning theory, 3814-3841, 2020
622020
Fast unsupervised bayesian image segmentation with adaptive spatial regularisation
M Pereyra, S McLaughlin
IEEE Transactions on Image processing 26 (6), 2577-2587, 2017
552017
Maximum likelihood estimation of regularization parameters in high-dimensional inverse problems: An empirical bayesian approach part i: Methodology and experiments
AF Vidal, V De Bortoli, M Pereyra, A Durmus
SIAM Journal on Imaging Sciences 13 (4), 1945-1989, 2020
522020
Modeling ultrasound echoes in skin tissues using symmetric α-stable processes
M Pereyra, H Batatia
IEEE transactions on ultrasonics, ferroelectrics, and frequency control 59 …, 2012
482012
Learned reconstruction methods with convergence guarantees: A survey of concepts and applications
S Mukherjee, A Hauptmann, O Öktem, M Pereyra, CB Schönlieb
IEEE Signal Processing Magazine 40 (1), 164-182, 2023
472023
Collaborative sparse regression using spatially correlated supports-application to hyperspectral unmixing
Y Altmann, M Pereyra, J Bioucas-Dias
IEEE Transactions on Image Processing 24 (12), 5800-5811, 2015
452015
Uncertainty quantification for radio interferometric imaging: II. MAP estimation
X Cai, M Pereyra, JD McEwen
Monthly Notices of the Royal Astronomical Society 480 (3), 4170-4182, 2018
432018
Bayesian nonlinear hyperspectral unmixing with spatial residual component analysis
Y Altmann, M Pereyra, S McLaughlin
IEEE Transactions on Computational Imaging 1 (3), 174-185, 2015
402015
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Articles 1–20