David Luengo

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Luca MartinoAssociate ProfessorVerified email at urjc.es
Víctor ElviraProfessor in Statistics and Data Science, University of EdinburghVerified email at ed.ac.uk
Ignacio SantamariaProfessor, Electrical Engineering, University of CantabriaVerified email at unican.es
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Mauricio A. ÁlvarezUniversity of ManchesterVerified email at manchester.ac.uk
Tom TriganoSenior Lecturer, SCE, Department of Electrical EngineeringVerified email at sce.ac.il
Antonio Artés RodríguezProfessor, Dept. of Signal Theory and Communications, Universidad Carlos III de MadridVerified email at tsc.uc3m.es
Jesse ReadÉcole PolytechniqueVerified email at polytechnique.edu
Gustau Camps-VallsProfessor. Image Processing Lab (IPL). Universitat de ValènciaVerified email at uv.es
Elena Dominguez-JimenezUniversidad Politécnica de MadridVerified email at upm.es
David Meltzer CaminoProfessor at Universidad Politécnica de MadridVerified email at upm.es
Jesús Ibáñez DíazAssociate professor, Universidad de CantabriaVerified email at unican.es
Jordi Muñoz-MaríProfessor. Electronic Engineering Department, University of ValenciaVerified email at uv.es
Michalis TitsiasDeepMindVerified email at google.com
Roberto CASARINCa' Foscari University of VeniceVerified email at unive.it
Gonzalo R. Ríos MuñozAssistant Professor, Univ. Carlos III de Madrid; IiSGM; CIBERCVVerified email at ing.uc3m.es
Javier VíaUniversidad de CantabriaVerified email at gtas.dicom.unican.es
Francisco LouzadaUniversidade de São PauloVerified email at icmc.usp.br
Daniel Heestermans SvendsenDIS CopenhagenVerified email at dis.dk
Manuel Campos-TabernerUniversitat de ValènciaVerified email at uv.es

David Luengo

Universidad Politécnica de Madrid (UPM)

Verified email at upm.es

Statistical Signal Processing Machine Learning Digital Communications Bayesian Inference Monte Carlo Methods


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Adaptive importance sampling: The past, the present, and the future MF Bugallo, V Elvira, L Martino, D Luengo, J Miguez, PM Djuric IEEE Signal Processing Magazine 34 (4), 60-79, 2017	273	2017
Latent force models M Alvarez, D Luengo, ND Lawrence Artificial intelligence and statistics, 9-16, 2009	237	2009
A survey of Monte Carlo methods for parameter estimation D Luengo, L Martino, M Bugallo, V Elvira, S Särkkä EURASIP Journal on Advances in Signal Processing 2020, 1-62, 2020	205	2020
Generalized multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo	194	2019
Efficient multioutput Gaussian processes through variational inducing kernels M Álvarez, D Luengo, M Titsias, ND Lawrence Proceedings of the Thirteenth International Conference on Artificial …, 2010	157	2010
Linear latent force models using Gaussian processes MA Álvarez, D Luengo, ND Lawrence IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 35 (11 …, 2013	145	2013
Efficient monte carlo methods for multi-dimensional learning with classifier chains J Read, L Martino, D Luengo Pattern Recognition 47 (3), 1535-1546, 2014	139	2014
Layered adaptive importance sampling L Martino, V Elvira, D Luengo, J Corander Statistics and Computing 27, 599-623, 2017	135	2017
Independent doubly adaptive rejection Metropolis sampling within Gibbs sampling L Martino, J Read, D Luengo IEEE Transactions on Signal Processing 63 (12), 3123-3138, 2015	115	2015
Scalable multi-output label prediction: From classifier chains to classifier trellises J Read, L Martino, PM Olmos, D Luengo Pattern Recognition 48 (6), 2096-2109, 2015	110	2015
Improving population Monte Carlo: Alternative weighting and resampling schemes V Elvira, L Martino, D Luengo, MF Bugallo Signal Processing 131, 77-91, 2017	106	2017
Orthogonal parallel MCMC methods for sampling and optimization L Martino, V Elvira, D Luengo, J Corander, F Louzada Digital Signal Processing 58, 64-84, 2016	100	2016
Independent random sampling methods L Martino, D Luengo, J Míguez Springer International Publishing, 2018	98	2018
Efficient multiple importance sampling estimators V Elvira, L Martino, D Luengo, MF Bugallo IEEE Signal Processing Letters 22 (10), 1757-1761, 2015	98	2015
An adaptive population importance sampler: Learning from uncertainty L Martino, V Elvira, D Luengo, J Corander IEEE Transactions on Signal Processing 63 (16), 4422-4437, 2015	97	2015
Physics-aware Gaussian processes in remote sensing G Camps-Valls, L Martino, DH Svendsen, M Campos-Taberner, ... Applied Soft Computing 68, 69-82, 2018	93	2018
Feature extraction of galvanic skin responses by nonnegative sparse deconvolution F Hernando-Gallego, D Luengo, A Artés-Rodríguez IEEE journal of biomedical and health informatics 22 (5), 1385-1394, 2017	72	2017
Efficient Monte Carlo optimization for multi-label classifier chains J Read, L Martino, D Luengo 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013	57	2013
Heretical multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo IEEE Signal Processing Letters 23 (10), 1474-1478, 2016	54	2016
A fast universal self-tuned sampler within Gibbs sampling L Martino, H Yang, D Luengo, J Kanniainen, J Corander Digital Signal Processing 47, 68-83, 2015	51	2015

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