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2019

Miguez, Joaquín; Lacasa, Lucas; Martínez-Ordóñez, José A.; Mariño, Inés P.

Multilayer Models of Random Sequences: Representability and Inference via Nonlinear Population Monte Carlo Artículo en actas

En: 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019.

Enlaces | BibTeX | Etiquetas: Markov chains, Multilayer networks, population Monte Carlo, random sequences

2018

Míguez, Joaquín; Mariño, Inés P.; Vázquez, Manuel A

Analysis of a nonlinear importance sampling scheme for Bayesian parameter estimation in state-space models Artículo de revista

En: Signal Processing, vol. 142, pp. 281-291, 2018, ISSN: 0165-1684.

Resumen | Enlaces | BibTeX | Etiquetas: Adaptive importance sampling, Bayesian inference, Importance sampling, Parameter estimation, population Monte Carlo, State space models

Míguez, Joaquín; Mariño, Inés P.; Vázquez, Manuel A

Analysis of a nonlinear importance sampling scheme for Bayesian parameter estimation in state-space models Artículo de revista

En: Signal Processing, vol. 142, pp. 281-291, 2018, ISSN: 0165-1684.

Resumen | Enlaces | BibTeX | Etiquetas: Adaptive importance sampling, Bayesian inference, Importance sampling, Parameter estimation, population Monte Carlo, State space models

2017

Elvira, Victor; Martino, Luca; Luengo, David; Bugallo, Monica F

Improving Population Monte Carlo: Alternative Weighting and Resampling Schemes Artículo de revista

En: Signal Processing, vol. 131, pp. 77–91, 2017, ISSN: 01651684.

Resumen | Enlaces | BibTeX | Etiquetas: Adaptive importance sampling, Journal, population Monte Carlo, Proposal distribution, Resampling

2015

Martino, Luca; Elvira, Victor; Luengo, David; Corander, Jukka

An Adaptive Population Importance Sampler: Learning From Uncertainty Artículo de revista

En: IEEE Transactions on Signal Processing, vol. 63, no. 16, pp. 4422–4437, 2015, ISSN: 1053-587X.

Resumen | Enlaces | BibTeX | Etiquetas: Adaptive importance sampling, adaptive multiple IS, adaptive population importance sampler, AMIS, APIS, Estimation, Importance sampling, IS estimators, iterative estimation, iterative methods, Journal, MC methods, Monte Carlo (MC) methods, Monte Carlo methods, population Monte Carlo, Proposals, Signal processing algorithms, simple temporal adaptation, Sociology, Standards, Wireless sensor network, Wireless Sensor Networks

Koblents, Eugenia; Miguez, Joaquin

A Population Monte Carlo Scheme with Transformed Weights and Its Application to Stochastic Kinetic Models Artículo de revista

En: Statistics and Computing, vol. 25, no. 2, pp. 407–425, 2015, ISSN: 0960-3174.

Resumen | Enlaces | BibTeX | Etiquetas: COMPREHENSION, degeneracy of importance weights, Importance sampling, Journal, population Monte Carlo, Stochastic kinetic models

2014

Koblents, Eugenia; Miguez, Joaquin

A Population Monte Carlo Scheme with Transformed Weights and Its Application to Stochastic Kinetic Models Artículo de revista

En: Statistics and Computing, no. (to appear), 2014, ISSN: 0960-3174.

Resumen | Enlaces | BibTeX | Etiquetas: degeneracy of importance weights, Importance sampling, population Monte Carlo, Stochastic kinetic models

Martino, Luca; Elvira, Víctor; Luengo, David; Artés-Rodríguez, Antonio; Corander, Jukka

Orthogonal MCMC Algorithms Artículo en actas

En: 2014 IEEE Workshop on Statistical Signal Processing (SSP 2014), Gold Coast, 2014.

Resumen | Enlaces | BibTeX | Etiquetas: Bayesian inference, Markov Chain Monte Carlo (MCMC), Parallel Chains, population Monte Carlo

2013

Koblents, Eugenia; Miguez, Joaquin

A Population Monte Carlo Scheme for Computational Inference in High Dimensional Spaces Artículo en actas

En: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 6318–6322, IEEE, Vancouver, 2013, ISSN: 1520-6149.

Resumen | Enlaces | BibTeX | Etiquetas: Approximation methods, computational inference, degeneracy of importance weights, high dimensional spaces, Importance sampling, importance weights, iterative importance sampling, iterative methods, mixture-PMC, mixture-PMC algorithm, Monte Carlo methods, MPMC, nonlinear transformations, population Monte Carlo, population Monte Carlo scheme, Probability density function, probability distributions, Proposals, Sociology, Standards