Marcelo Pereyra

88 papers A* 2A 1B 1Misc 1Journal 63Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep unfolding of MCMC kernels: scalable, modular & explainable GANs for high-dimensional posterior sampling. CoRR Jonathan Spence, Tobías I. Liaudat, Konstantinos Zygalakis, Marcelo Pereyra
2026	J	`jnl`	Integrative Nutritional Assessment of Avocado Leaves Using Entropy-Weighted Spectral Indices and Fusion Learning. Comput. Zhen Guo, Juan Sebastian Estrada, Xingfeng Guo, Redmond R. Shamshiri, Marcelo Pereyra, Fernando Auat Cheein
2025	J	`jnl`	Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements. CoRR Tom Sprunck, Marcelo Pereyra, Tobías I. Liaudat
2025	J	`jnl`	Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems. CoRR Teresa Klatzer, Savvas Melidonis, Marcelo Pereyra, Konstantinos C. Zygalakis
2025	J	`jnl`	Empirical Bayesian Image Restoration by Langevin Sampling with a Denoising Diffusion Implicit Prior. J. Math. Imaging Vis. Charlesquin Kemajou Mbakam, Jean-François Giovannelli, Marcelo Pereyra
2025	J	`jnl`	Hypothesis Testing in Imaging Inverse Problems. CoRR Yiming Xi, Konstantinos Zygalakis, Marcelo Pereyra
2025	J	`jnl`	LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimization. CoRR Alessio Spagnoletti, Jean Prost, Andrés Almansa, Nicolas Papadakis, Marcelo Pereyra
2025	J	`jnl`	LVTINO: LAtent Video consisTency INverse sOlver for High Definition Video Restoration. CoRR Alessio Spagnoletti, Andrés Almansa, Marcelo Pereyra
2025	J	`jnl`	Learning few-step posterior samplers by unfolding and distillation of diffusion models. CoRR Charlesquin Kemajou Mbakam, Jonathan Spence, Marcelo Pereyra
2025	J	`jnl`	Learning few-step posterior samplers by unfolding and distillation of diffusion models. Trans. Mach. Learn. Res. Charlesquin Kemajou Mbakam, Marcelo Pereyra, Jonathan Spence
2025	—	`ed.`	Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part I SSVM (1) Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb
2025	—	`ed.`	Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part II SSVM (2) Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb
2025	J	`jnl`	Score-Based Denoising Diffusion Models for Photon-Starved Image Restoration Problems. Trans. Mach. Learn. Res. Savvas Melidonis, Yiming Xi, Konstantinos C. Zygalakis, Yoann Altmann, Marcelo Pereyra
2025	—	`conf`	Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems. SSVM (1) Jasper M. Everink, Bernardin Tamo Amougou, Marcelo Pereyra
2025	J	`jnl`	Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems. CoRR Jasper M. Everink, Bernardin Tamo Amougou, Marcelo Pereyra
2025	—	`conf`	Self-supervised conformal prediction for uncertainty quantification in Poisson imaging problems. SSP Bernardin Tamo Amougou, Marcelo Pereyra, Barbara Pascal
2025	J	`jnl`	Self-supervised conformal prediction for uncertainty quantification in Poisson imaging problems. CoRR Bernardin Tamo Amougou, Marcelo Pereyra, Barbara Pascal
2025	J	`jnl`	Uncertainty Estimation for Learning-Based Classification of Corrupted Images. SIAM J. Imaging Sci. Alexander Effland, Erich Kobler, Marcelo Pereyra, J. Peter
2024	J	`jnl`	Accelerated Bayesian Imaging by Relaxed Proximal-Point Langevin Sampling. SIAM J. Imaging Sci. Teresa Klatzer, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Jesús María Sanz-Serna, Konstantinos C. Zygalakis
2024	J	`jnl`	Bayesian computation with generative diffusion models by Multilevel Monte Carlo. CoRR Abdul-Lateef Haji-Ali, Marcelo Pereyra, Luke Shaw, Konstantinos Zygalakis
2024	J	`jnl`	Do Bayesian imaging methods report trustworthy probabilities? CoRR David Y. W. Thong, Charlesquin Kemajou Mbakam, Marcelo Pereyra
2024	J	`jnl`	Empirical Bayesian Imaging With Large-Scale Push-Forward Generative Priors. IEEE Signal Process. Lett. Savvas Melidonis, Matthew Holden, Yoann Altmann, Marcelo Pereyra, Konstantinos C. Zygalakis
2024	J	`jnl`	Empirical Bayesian image restoration by Langevin sampling with a denoising diffusion implicit prior. CoRR Charlesquin Kemajou Mbakam, Jean-François Giovannelli, Marcelo Pereyra
2024	A	`conf`	Equivariant bootstrapping for uncertainty quantification in imaging inverse problems. AISTATS Marcelo Pereyra, Julián Tachella
2024	J	`jnl`	Marginal Likelihood Estimation in Semiblind Image Deconvolution: A Stochastic Approximation Approach. SIAM J. Imaging Sci. Charlesquin Kemajou Mbakam, Marcelo Pereyra, Jean-François Giovannelli
2024	J	`jnl`	Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. CoRR Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. Trans. Mach. Learn. Res. Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling. CoRR Teresa Klatzer, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Jesús María Sanz-Serna, Konstantinos C. Zygalakis
2023	J	`jnl`	Efficient Bayesian Computation for Low-Photon Imaging Problems. SIAM J. Imaging Sci. Savvas Melidonis, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Konstantinos Zygalakis
2023	J	`jnl`	Equivariant Bootstrapping for Uncertainty Quantification in Imaging Inverse Problems. CoRR Julián Tachella, Marcelo Pereyra
2023	J	`jnl`	Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications. IEEE Signal Process. Mag. Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
2023	J	`jnl`	On Maximum a Posteriori Estimation with Plug & Play Priors and Stochastic Gradient Descent. J. Math. Imaging Vis. Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2023	J	`jnl`	Scalable Bayesian uncertainty quantification with data-driven priors for radio interferometric imaging. CoRR Tobías I. Liaudat, Matthijs Mars, Matthew A. Price, Marcelo Pereyra, Marta M. Betcke, Jason D. McEwen
2023	J	`jnl`	The Split Gibbs Sampler Revisited: Improvements to Its Algorithmic Structure and Augmented Target Distribution. SIAM J. Imaging Sci. Marcelo Pereyra, Luis Vargas Mieles, Konstantinos C. Zygalakis
2022	J	`jnl`	A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau. SIAM Rev. Alain Durmus, Éric Moulines, Marcelo Pereyra
2022	J	`jnl`	Bayesian Imaging Using Plug & Play Priors: When Langevin Meets Tweedie. SIAM J. Imaging Sci. Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2022	J	`jnl`	Bayesian Imaging with Data-Driven Priors Encoded by Neural Networks. SIAM J. Imaging Sci. Matthew Holden, Marcelo Pereyra, Konstantinos C. Zygalakis
2022	J	`jnl`	Learned reconstruction with convergence guarantees. CoRR Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
2022	J	`jnl`	On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent. CoRR Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2022	J	`jnl`	Proximal nested sampling for high-dimensional Bayesian model selection. Stat. Comput. Xiaohao Cai, Jason D. McEwen, Marcelo Pereyra
2021	J	`jnl`	Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms. CoRR Matthew Holden, Marcelo Pereyra, Konstantinos C. Zygalakis
2021	—	`conf`	Bayesian Model Selection for Unsupervised Image Deconvolution with Structured Gaussian Priors. SSP Benjamin Harroué, Jean-François Giovannelli, Marcelo Pereyra
2021	J	`jnl`	Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie. CoRR Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra
2021	J	`jnl`	Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Stat. Comput. Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal
2021	—	`conf`	Fast Bayesian Model Selection in Imaging Inverse Problems Using Residuals. SSP Ana Fernandez Vidal, Marcelo Pereyra, Alain Durmus, Jean-François Giovannelli
2020	J	`jnl`	Accelerating Proximal Markov Chain Monte Carlo by Using an Explicit Stabilized Method. SIAM J. Imaging Sci. Marcelo Pereyra, Luis Vargas Mieles, Konstantinos C. Zygalakis
2020	J	`jnl`	Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments. SIAM J. Imaging Sci. Ana Fernandez Vidal, Valentin De Bortoli, Marcelo Pereyra, Alain Durmus
2020	J	`jnl`	Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis. SIAM J. Imaging Sci. Valentin De Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal
2020	A*	`conf`	Wasserstein Control of Mirror Langevin Monte Carlo. COLT Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra
2020	J	`jnl`	Wasserstein Control of Mirror Langevin Monte Carlo. CoRR Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra
2019	J	`jnl`	Accelerating proximal Markov chain Monte Carlo by using explicit stabilised methods. CoRR Luis Vargas, Marcelo Pereyra, Konstantinos C. Zygalakis
2019	—	`conf`	Quantifying Uncertainty in High Dimensional Inverse Problems by Convex Optimisation. EUSIPCO Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
2019	J	`jnl`	Revisiting Maximum-A-Posteriori Estimation in Log-Concave Models. SIAM J. Imaging Sci. Marcelo Pereyra
2019	J	`jnl`	Scalable Bayesian Uncertainty Quantification in Imaging Inverse Problems via Convex Optimization. SIAM J. Imaging Sci. Audrey Repetti, Marcelo Pereyra, Yves Wiaux
2018	—	`conf`	Bayesian Restoration of High-Dimensional Photon-Starved Images. EUSIPCO Julián Tachella, Yoann Altmann, Marcelo Pereyra, Stephen McLaughlin, Jean-Yves Tourneret
2018	J	`jnl`	Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau. SIAM J. Imaging Sci. Alain Durmus, Eric Moulines, Marcelo Pereyra
2018	B	`conf`	Maximum Likelihood Estimation of Regularisation Parameters. ICIP Ana Fernandez Vidal, Marcelo Pereyra
2018	—	`conf`	Uncertainty Quantification in Imaging: When Convex Optimization Meets Bayesian Analysis. EUSIPCO Audrey Repetti, Marcelo Pereyra, Yves Wiaux
2017	J	`jnl`	Fast Unsupervised Bayesian Image Segmentation With Adaptive Spatial Regularisation. IEEE Trans. Image Process. Marcelo Pereyra, Stephen McLaughlin
2017	J	`jnl`	Maximum-a-Posteriori Estimation with Bayesian Confidence Regions. SIAM J. Imaging Sci. Marcelo Pereyra
2017	A*	`conf`	Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo. COLT Nicolas Brosse, Alain Durmus, Eric Moulines, Marcelo Pereyra
2017	J	`jnl`	Uncertainty quantification for radio interferometric imaging: I. proximal MCMC methods. CoRR Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
2017	J	`jnl`	Uncertainty quantification for radio interferometric imaging: II. MAP estimation. CoRR Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
2016	J	`jnl`	A Survey of Stochastic Simulation and Optimization Methods in Signal Processing. IEEE J. Sel. Top. Signal Process. Marcelo Pereyra, Philip Schniter, Emilie Chouzenoux, Jean-Christophe Pesquet, Jean-Yves Tourneret, Alfred O. Hero III, Steve McLaughlin
2016	—	`conf`	Approximating Bayesian confidence regions in convex inverse problems. SSP Marcelo Pereyra
2016	—	`conf`	Comparing Bayesian models in the absence of ground truth. EUSIPCO Marcelo Pereyra, Steve McLaughlin
2016	J	`jnl`	Introduction to the Issue on Stochastic Simulation and Optimization in Signal Processing. IEEE J. Sel. Top. Signal Process. Steve McLaughlin, Marcelo Pereyra, Alfred O. Hero III, Jean-Yves Tourneret, Jean-Christophe Pesquet
2016	—	`conf`	Multivariate Bayesian classification of epilepsy EEG signals. IVMSP Antonio Quintero-Rincón, Jorge Prendes, Marcelo Pereyra, Hadj Batatia, Marcelo R. Risk
2016	J	`jnl`	Proximal Markov chain Monte Carlo algorithms. Stat. Comput. Marcelo Pereyra
2015	J	`jnl`	Bayesian Nonlinear Hyperspectral Unmixing With Spatial Residual Component Analysis. IEEE Trans. Computational Imaging Yoann Altmann, Marcelo Pereyra, Stephen McLaughlin
2015	J	`jnl`	Bayesian computation: a summary of the current state, and samples backwards and forwards. Stat. Comput. Peter J. Green, Krzysztof Latuszynski, Marcelo Pereyra, Christian P. Robert
2015	J	`jnl`	Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing. IEEE Trans. Image Process. Yoann Altmann, Marcelo Pereyra, José M. Bioucas-Dias
2015	J	`jnl`	Exploiting Information Geometry to Improve the Convergence of Nonparametric Active Contours. IEEE Trans. Image Process. Marcelo Pereyra, Hadj Batatia, Steve McLaughlin
2015	J	`jnl`	Fast unsupervised Bayesian image segmentation with adaptive spatial regularisation. CoRR Marcelo Pereyra, Steve McLaughlin
2015	—	`conf`	Linear spectral unmixing using collaborative sparse regression and correlated supports. WHISPERS Yoann Altmann, Marcelo Pereyra, José M. Bioucas-Dias
2015	—	`conf`	Maximum-a-posteriori estimation with unknown regularisation parameters. EUSIPCO Marcelo Pereyra, José M. Bioucas-Dias, Mário A. T. Figueiredo
2015	—	`conf`	Nonlinear spectral unmixing using residual component analysis and a Gamma Markov random field. CAMSAP Yoann Altmann, Marcelo Pereyra, Steve McLaughlin
2015	J	`jnl`	Tutorial on Stochastic Simulation and Optimization Methods in Signal Processing. CoRR Marcelo Pereyra, Philip Schniter, Emilie Chouzenoux, Jean-Christophe Pesquet, Jean-Yves Tourneret, Alfred O. Hero III, Steve McLaughlin
2014	J	`jnl`	Computing the Cramer-Rao Bound of Markov Random Field Parameters: Application to the Ising and the Potts Models. IEEE Signal Process. Lett. Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
2014	—	`conf`	Maximum marginal likelihood estimation of the granularity coefficient of a Potts-Markov random field within an MCMC algorithm. SSP Marcelo Pereyra, Nick Whiteley, Christophe Andrieu, Jean-Yves Tourneret
2014	—	`conf`	Small-variance asymptotics of hidden Potts-MRFS: Application to fast Bayesian image segmentation. EUSIPCO Marcelo Pereyra, Steve McLaughlin
2013	J	`jnl`	Estimating the Granularity Coefficient of a Potts-Markov Random Field Within a Markov Chain Monte Carlo Algorithm. IEEE Trans. Image Process. Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
2013	J	`jnl`	Exploiting Information Geometry to Improve the Convergence Properties of Variational Active Contours. IEEE J. Sel. Top. Signal Process. Marcelo Pereyra, Hadj Batatia, Steve McLaughlin
2013	—	`conf`	Exploiting information geometry to improve the convergence of nonparametric active contours. CAMSAP Marcelo Pereyra, Hadj Batatia, Steve McLaughlin
2012	J	`jnl`	Segmentation of Skin Lesions in 2-D and 3-D Ultrasound Images Using a Spatially Coherent Generalized Rayleigh Mixture Model. IEEE Trans. Medical Imaging Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
2012	—	`—`	Statistical modeling and processing of high frequency ultrasound images: Application to dermatologic oncology. (Modélisation et traitement statistiques d'images d'ultrasons de haute fréquence. Application à l'oncologie dermatologique). Marcelo Pereyra
2011	Misc	`conf`	Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture model. ICASSP Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
2011	—	`conf`	Segmentation of ultrasound images using a spatially coherent generalized Rayleigh mixture model. EUSIPCO Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret