David Luengo - Google Scholar Citations

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	All	Since 2014
Citations	1377	1122
h-index	21	19
i10-index	35	27

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Luca MartinoUniversidad Rey Juan Carlos (URJC)Verified email at urjc.es
Víctor ElviraReader (Associate Professor), University of EdinburghVerified email at ed.ac.uk
Ignacio SantamariaProfessor, Electrical Engineering, University of CantabriaVerified email at unican.es
Neil D. LawrenceAmazonVerified email at sheffield.ac.uk
Mauricio A. ÁlvarezUniversity of SheffieldVerified email at sheffield.ac.uk
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
Tom TriganoSenior Lecturer, SCE, Department of Electrical EngineeringVerified email at sce.ac.il
Jesús Ibáñez DíazAssociate professor, Universidad de CantabriaVerified email at unican.es
Elena Dominguez-JimenezUniversidad Politécnica de MadridVerified email at upm.es
Michalis TitsiasDeepMindVerified email at google.com
Roberto CASARINUniversity Ca' Foscari of VeniceVerified email at unive.it
Francisco LouzadaUniversidade de São PauloVerified email at icmc.usp.br
Fabrizio LeisenReader in Statistics-University of KentVerified email at kent.ac.uk
Javier VíaUniversidad de CantabriaVerified email at gtas.dicom.unican.es
Fernando Cruz-RoldánProfessorVerified email at uah.es
David Meltzer CaminoProfessor at Universidad Politécnica de MadridVerified email at upm.es
Pablo M. OlmosUniversity Carlos III de MadridVerified email at tsc.uc3m.es
Gustau Camps-VallsFull Professor. Image Processing Laboratory (IPL). Universitat de València.Verified email at uv.es
Gonzalo R. Ríos MuñozDepartment of Signal Processing, Universidad Carlos III de MadridVerified email at tsc.uc3m.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


Title	Cited by	Year
Latent force models M Alvarez, D Luengo, ND Lawrence Artificial Intelligence and Statistics, 9-16, 2009	108	2009
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	78	2010
Efficient monte carlo methods for multi-dimensional learning with classifier chains J Read, L Martino, D Luengo Pattern Recognition 47 (3), 1535-1546, 2014	72	2014
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	56	2013
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	52	2015
Generalized multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo arXiv preprint arXiv:1511.03095, 2015	51*	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	50	2015
Layered adaptive importance sampling L Martino, V Elvira, D Luengo, J Corander Statistics and Computing 27 (3), 599-623, 2017	49	2017
Efficient multiple importance sampling estimators V Elvira, L Martino, D Luengo, MF Bugallo IEEE Signal Processing Letters 22 (10), 1757-1761, 2015	48	2015
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	46	2015
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	40	2016
Improving population Monte Carlo: Alternative weighting and resampling schemes V Elvira, L Martino, D Luengo, MF Bugallo Signal Processing 131, 77-91, 2017	39	2017
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	37	2017
Secure communications using OFDM with chaotic modulation in the subcarriers D Luengo, I Santamaria 2005 IEEE 61st Vehicular Technology Conference 2, 1022-1026, 2005	37	2005
Fully adaptive gaussian mixture metropolis-hastings algorithm D Luengo, L Martino 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013	34	2013
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	32	2013
Heretical multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo IEEE Signal Processing Letters 23 (10), 1474-1478, 2016	31	2016
Optimal Estimation of Chaotic Signals Generated by Piecewise-Linear Maps C Pantaleón, D Luengo, I Santamaría Signal Processing Letters, IEEE 7 (8), 235-237, 2000	29*	2000
Independent doubly adaptive rejection Metropolis sampling L Martino, J Read, D Luengo 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014	26	2014
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	24	2015

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