Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals

3 January 2025

Papers citing "Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals"

25 / 25 papers shown

Title
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data Samuel Rey Ernesto Curbelo Luca Martino F. Llorente Antonio G. Marques 88 0 0 25 Mar 2025
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming Yongquan Qu Mohamed Aziz Bhouri Pierre Gentine AI4CE 101 4 0 04 Mar 2024
Gradient-based Adaptive Importance Samplers Victor Elvira Émilie Chouzenoux Ömer Deniz Akyildiz Luca Martino DiffM 101 10 0 19 Oct 2022
On the safe use of prior densities for Bayesian model selection F. Llorente Luca Martino E. Curbelo J. Lopez-Santiago D. Delgado 123 17 0 10 Jun 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 105 5 0 07 Jan 2022
A Survey of Monte Carlo Methods for Parameter Estimation D. Luengo Luca Martino M. Bugallo Victor Elvira S. Särkkä 95 158 0 25 Jul 2021
Automatic tempered posterior distributions for Bayesian inversion problems Luca Martino F. Llorente E. Curbelo J. Lopez-Santiago Joaquín Míguez 73 13 0 24 Jul 2021
Compressed Monte Carlo with application in particle filtering Luca Martino Victor Elvira 81 36 0 18 Jul 2021
MCMC-driven importance samplers F. Llorente E. Curbelo Luca Martino Victor Elvira D. Delgado 113 11 0 06 May 2021
Deep Importance Sampling based on Regression for Model Inversion and Emulation F. Llorente Luca Martino D. Delgado G. Camps-Valls 86 19 0 20 Oct 2020
Marginal likelihood computation for model selection and hypothesis testing: an extensive review F. Llorente Luca Martino D. Delgado J. Lopez-Santiago 107 86 0 17 May 2020
The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent Xin-Yao Qian Diego Klabjan ODL 72 36 0 27 Apr 2020
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization Ömer Deniz Akyildiz Dan Crisan Joaquín Míguez 72 6 0 23 Nov 2018
User-Friendly Covariance Estimation for Heavy-Tailed Distributions Y. Ke Stanislav Minsker Zhao Ren Qiang Sun Wen-Xin Zhou 113 57 0 05 Nov 2018
Robust Covariance Adaptation in Adaptive Importance Sampling Yousef El-Laham Victor Elvira M. Bugallo 90 17 0 31 May 2018
A Review of Multiple Try MCMC algorithms for Signal Processing Luca Martino 76 82 0 27 Jan 2018
Metropolis Sampling Luca Martino Victor Elvira 92 25 0 15 Apr 2017
The Recycling Gibbs Sampler for Efficient Learning Luca Martino Victor Elvira Gustau Camps-Valls 96 30 0 21 Nov 2016
Langevin Incremental Mixture Importance Sampling Matteo Fasiolo Flávio Eler De Melo Simon Maskell 53 13 0 21 Nov 2016
Effective Sample Size for Importance Sampling based on discrepancy measures Luca Martino Victor Elvira F. Louzada 167 181 0 10 Feb 2016
Generalized Multiple Importance Sampling Victor Elvira Luca Martino D. Luengo M. Bugallo 121 146 0 10 Nov 2015
Gradient Importance Sampling Ingmar Schuster 89 25 0 21 Jul 2015
Layered Adaptive Importance Sampling Luca Martino Victor Elvira D. Luengo J. Corander 99 108 0 18 May 2015
Asymptotically Exact, Embarrassingly Parallel MCMC Willie Neiswanger Chong-Jun Wang Eric Xing FedML 120 330 0 19 Nov 2013
Adaptive Multiple Importance Sampling J. Cornuet Jean-Michel Marin Antonietta Mira Christian P. Robert 171 264 0 07 Jul 2009