Marcelo Pereyra

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 48

Top Venues

National Polytechnic Institute of Toulouse, France (PHD)

Education History

National Polytechnic Institute of Toulouse, France

PHD

Publications

Savvas Melidonis, Matthew Holden, Yoann Altmann, Marcelo Pereyra, Konstantinos C. Zygalakis
Empirical Bayesian Imaging With Large-Scale Push-Forward Generative Priors. IEEE Signal Process. Lett. 31 (2024)
Teresa Klatzer, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Jesús María Sanz-Serna, Konstantinos C. Zygalakis
Accelerated Bayesian Imaging by Relaxed Proximal-Point Langevin Sampling. SIAM J. Imaging Sci. 17 (2) (2024)
Charlesquin Kemajou Mbakam, Marcelo Pereyra, Jean-François Giovannelli
Marginal Likelihood Estimation in Semiblind Image Deconvolution: A Stochastic Approximation Approach. SIAM J. Imaging Sci. 17 (2) (2024)
Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. CoRR (2024)
David Y. W. Thong, Charlesquin Kemajou Mbakam, Marcelo Pereyra
Do Bayesian imaging methods report trustworthy probabilities? CoRR (2024)
Marcelo Pereyra, Julián Tachella
Equivariant bootstrapping for uncertainty quantification in imaging inverse problems. AISTATS (2024)
Savvas Melidonis, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Konstantinos Zygalakis
Efficient Bayesian Computation for Low-Photon Imaging Problems. SIAM J. Imaging Sci. 16 (3) (2023)
Tobías I. Liaudat, Matthijs Mars, Matthew A. Price, Marcelo Pereyra, Marta M. Betcke, Jason D. McEwen
Scalable Bayesian uncertainty quantification with data-driven priors for radio interferometric imaging. CoRR (2023)
Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications. IEEE Signal Process. Mag. 40 (1) (2023)
Julián Tachella, Marcelo Pereyra
Equivariant Bootstrapping for Uncertainty Quantification in Imaging Inverse Problems. CoRR (2023)
Marcelo Pereyra, Luis Vargas Mieles, Konstantinos C. Zygalakis
The Split Gibbs Sampler Revisited: Improvements to Its Algorithmic Structure and Augmented Target Distribution. SIAM J. Imaging Sci. 16 (4) (2023)
Teresa Klatzer, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Jesús María Sanz-Serna, Konstantinos C. Zygalakis
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling. CoRR (2023)
Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
On Maximum a Posteriori Estimation with Plug & Play Priors and Stochastic Gradient Descent. J. Math. Imaging Vis. 65 (1) (2023)
Matthew Holden, Marcelo Pereyra, Konstantinos C. Zygalakis
Bayesian Imaging with Data-Driven Priors Encoded by Neural Networks. SIAM J. Imaging Sci. 15 (2) (2022)
Alain Durmus, Éric Moulines, Marcelo Pereyra
A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau. SIAM Rev. 64 (4) (2022)
Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
Bayesian Imaging Using Plug & Play Priors: When Langevin Meets Tweedie. SIAM J. Imaging Sci. 15 (2) (2022)
Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent. CoRR (2022)
Xiaohao Cai, Jason D. McEwen, Marcelo Pereyra
Proximal nested sampling for high-dimensional Bayesian model selection. Stat. Comput. 32 (5) (2022)
Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
Learned reconstruction with convergence guarantees. CoRR (2022)
Benjamin Harroué, Jean-François Giovannelli, Marcelo Pereyra
Bayesian Model Selection for Unsupervised Image Deconvolution with Structured Gaussian Priors. SSP (2021)
Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie. CoRR (2021)
Ana Fernandez Vidal, Marcelo Pereyra, Alain Durmus, Jean-François Giovannelli
Fast Bayesian Model Selection in Imaging Inverse Problems Using Residuals. SSP (2021)
Matthew Holden, Marcelo Pereyra, Konstantinos C. Zygalakis
Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms. CoRR (2021)
Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Stat. Comput. 31 (3) (2021)
Ana Fernandez Vidal, Valentin De Bortoli, Marcelo Pereyra, Alain Durmus
Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments. SIAM J. Imaging Sci. 13 (4) (2020)
Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra
Wasserstein Control of Mirror Langevin Monte Carlo. COLT (2020)
Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal
Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis. SIAM J. Imaging Sci. 13 (4) (2020)
Marcelo Pereyra, Luis Vargas Mieles, Konstantinos C. Zygalakis
Accelerating Proximal Markov Chain Monte Carlo by Using an Explicit Stabilized Method. SIAM J. Imaging Sci. 13 (2) (2020)
Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra
Wasserstein Control of Mirror Langevin Monte Carlo. CoRR (2020)
Audrey Repetti, Marcelo Pereyra, Yves Wiaux
Scalable Bayesian Uncertainty Quantification in Imaging Inverse Problems via Convex Optimization. SIAM J. Imaging Sci. 12 (1) (2019)
Marcelo Pereyra
Revisiting Maximum-A-Posteriori Estimation in Log-Concave Models. SIAM J. Imaging Sci. 12 (1) (2019)
Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
Quantifying Uncertainty in High Dimensional Inverse Problems by Convex Optimisation. EUSIPCO (2019)
Luis Vargas, Marcelo Pereyra, Konstantinos C. Zygalakis
Accelerating proximal Markov chain Monte Carlo by using explicit stabilised methods. CoRR (2019)
Audrey Repetti, Marcelo Pereyra, Yves Wiaux
Uncertainty Quantification in Imaging: When Convex Optimization Meets Bayesian Analysis. EUSIPCO (2018)
Ana Fernandez Vidal, Marcelo Pereyra
Maximum Likelihood Estimation of Regularisation Parameters. ICIP (2018)
Alain Durmus, Eric Moulines, Marcelo Pereyra
Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau. SIAM J. Imaging Sci. 11 (1) (2018)
Julián Tachella, Yoann Altmann, Marcelo Pereyra, Stephen McLaughlin, Jean-Yves Tourneret
Bayesian Restoration of High-Dimensional Photon-Starved Images. EUSIPCO (2018)
Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
Uncertainty quantification for radio interferometric imaging: I. proximal MCMC methods. CoRR (2017)
Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
Uncertainty quantification for radio interferometric imaging: II. MAP estimation. CoRR (2017)
Marcelo Pereyra
Maximum-a-Posteriori Estimation with Bayesian Confidence Regions. SIAM J. Imaging Sci. 10 (1) (2017)
Marcelo Pereyra, Stephen McLaughlin
Fast Unsupervised Bayesian Image Segmentation With Adaptive Spatial Regularisation. IEEE Trans. Image Process. 26 (6) (2017)
Nicolas Brosse, Alain Durmus, Eric Moulines, Marcelo Pereyra
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo. COLT (2017)
Marcelo Pereyra
Proximal Markov chain Monte Carlo algorithms. Stat. Comput. 26 (4) (2016)
Antonio Quintero-Rincón, Jorge Prendes, Marcelo Pereyra, Hadj Batatia, Marcelo R. Risk
Multivariate Bayesian classification of epilepsy EEG signals. IVMSP (2016)
Marcelo Pereyra
Approximating Bayesian confidence regions in convex inverse problems. SSP (2016)
Marcelo Pereyra, Steve McLaughlin
Comparing Bayesian models in the absence of ground truth. EUSIPCO (2016)
Steve McLaughlin, Marcelo Pereyra, Alfred O. Hero III, Jean-Yves Tourneret, Jean-Christophe Pesquet
Introduction to the Issue on Stochastic Simulation and Optimization in Signal Processing. IEEE J. Sel. Top. Signal Process. 10 (2) (2016)
Marcelo Pereyra, Philip Schniter, Émilie Chouzenoux, Jean-Christophe Pesquet, Jean-Yves Tourneret, Alfred O. Hero III, Steve McLaughlin
A Survey of Stochastic Simulation and Optimization Methods in Signal Processing. IEEE J. Sel. Top. Signal Process. 10 (2) (2016)
Marcelo Pereyra, Steve McLaughlin
Fast unsupervised Bayesian image segmentation with adaptive spatial regularisation. CoRR (2015)
Yoann Altmann, Marcelo Pereyra, José M. Bioucas-Dias
Linear spectral unmixing using collaborative sparse regression and correlated supports. WHISPERS (2015)
Yoann Altmann, Marcelo Pereyra, Stephen McLaughlin
Bayesian Nonlinear Hyperspectral Unmixing With Spatial Residual Component Analysis. IEEE Trans. Computational Imaging 1 (3) (2015)
Yoann Altmann, Marcelo Pereyra, José M. Bioucas-Dias
Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing. IEEE Trans. Image Process. 24 (12) (2015)
Marcelo Pereyra, José M. Bioucas-Dias, Mário A. T. Figueiredo
Maximum-a-posteriori estimation with unknown regularisation parameters. EUSIPCO (2015)
Yoann Altmann, Marcelo Pereyra, Steve McLaughlin
Nonlinear spectral unmixing using residual component analysis and a Gamma Markov random field. CAMSAP (2015)
Peter J. Green, Krzysztof Latuszynski, Marcelo Pereyra, Christian P. Robert
Bayesian computation: a summary of the current state, and samples backwards and forwards. Stat. Comput. 25 (4) (2015)
Marcelo Pereyra, Philip Schniter, Émilie Chouzenoux, Jean-Christophe Pesquet, Jean-Yves Tourneret, Alfred O. Hero III, Steve McLaughlin
Tutorial on Stochastic Simulation and Optimization Methods in Signal Processing. CoRR (2015)
Marcelo Pereyra, Hadj Batatia, Steve McLaughlin
Exploiting Information Geometry to Improve the Convergence of Nonparametric Active Contours. IEEE Trans. Image Process. 24 (3) (2015)
Marcelo Pereyra, Nick Whiteley, Christophe Andrieu, Jean-Yves Tourneret
Maximum marginal likelihood estimation of the granularity coefficient of a Potts-Markov random field within an MCMC algorithm. SSP (2014)
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
Computing the Cramer-Rao Bound of Markov Random Field Parameters: Application to the Ising and the Potts Models. IEEE Signal Process. Lett. 21 (1) (2014)
Marcelo Pereyra, Steve McLaughlin
Small-variance asymptotics of hidden Potts-MRFS: Application to fast Bayesian image segmentation. EUSIPCO (2014)
Marcelo Pereyra, Hadj Batatia, Steve McLaughlin
Exploiting Information Geometry to Improve the Convergence Properties of Variational Active Contours. IEEE J. Sel. Top. Signal Process. 7 (4) (2013)
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
Estimating the Granularity Coefficient of a Potts-Markov Random Field Within a Markov Chain Monte Carlo Algorithm. IEEE Trans. Image Process. 22 (6) (2013)
Marcelo Pereyra, Hadj Batatia, Steve McLaughlin
Exploiting information geometry to improve the convergence of nonparametric active contours. CAMSAP (2013)
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
Segmentation of Skin Lesions in 2-D and 3-D Ultrasound Images Using a Spatially Coherent Generalized Rayleigh Mixture Model. IEEE Trans. Medical Imaging 31 (8) (2012)
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture model. ICASSP (2011)
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
Segmentation of ultrasound images using a spatially coherent generalized Rayleigh mixture model. EUSIPCO (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Marcelo Pereyra