Eugenia Koblents
Eugenia Koblents
Senior Machine Learning Scientist, United Technologies Research Center Ireland
Verified email at utrc.utc.com
Title
Cited by
Cited by
Year
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
E Koblents, J Míguez
Statistics and Computing 25 (2), 407-425, 2015
782015
A nonlinear population Monte Carlo scheme for the Bayesian estimation of parameters of α-stable distributions
E Koblents, J Míguez, MA Rodríguez, AM Schmidt
Computational Statistics & Data Analysis 95, 57-74, 2016
212016
Robust mixture populationmonte Carlo scheme with adaptation of the number of components
E Koblents, J Míguez
21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013
62013
A population Monte Carlo method for Bayesian inference and its application to stochastic kinetic models
E Koblents, J Míguez
2011 19th European Signal Processing Conference, 679-683, 2011
62011
A comparison of nonlinear population Monte Carlo and particle Markov Chain Monte Carlo algorithms for Bayesian inference in stochastic kinetic models
E Koblents, J Míguez
arXiv preprint arXiv:1404.5218, 2014
52014
A population monte carlo scheme for computational inference in high dimensional spaces
E Koblents, J Míguez
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
52013
Bayesian computation methods for inference in stochastic kinetic models
E Koblents, IP Mariño, J Míguez
Complexity 2019, 2019
22019
Particle filtering with transformed weights
J Míguez, E Koblents
2013 5th IEEE International Workshop on Computational Advances in Multi …, 2013
22013
This is a postprint version of the following published document
E Koblents, J Míguez, MA Rodríguez, A Schmidtd
Computational Statistics & Data Analysis 95, 57-74, 2016
2016
A nonlinear population Monte Carlo scheme for the Bayesian estimation of parameters of alpha-stable distributions
E Koblents Lapteva, J Míguez Arenas, MA Rodríguez, AM Schmidt
Elsevier, 2016
2016
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
E Koblents Lapteva, J Míguez Arenas
Springer, 2015
2015
Nonlinear population Monte Carlo methods for bayesian inference
E Koblents Lápteva
2015
A comparison of nonlinear population Monte Carlo and particle Markov chain Monte Carlo algorithms for Bayesian inference in stochastic kinetic models
E Koblents Lapteva, J Míguez Arenas
Cornell University, 2014
2014
Importance sampling with transformed weights
E Koblents, J Míguez
2012
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Articles 1–14