Víctor Elvira

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	All	Since 2015
Citations	1422	1268
h-index	21	18
i10-index	32	29

340

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Co-authors

Luca MartinoUniversidad Rey Juan Carlos (URJC)Verified email at urjc.es
David LuengoUniversidad Politécnica de Madrid (UPM)Verified email at upm.es
Ignacio SantamariaProfessor, Electrical Engineering, University of CantabriaVerified email at unican.es
Francisco LouzadaUniversidade de São PauloVerified email at icmc.usp.br
Javier VíaUniversidad de CantabriaVerified email at gtas.dicom.unican.es
Joaquin MiguezDepartment of Signal Theory & Communications, Universidad Carlos III de MadridVerified email at tsc.uc3m.es
Gustau Camps-VallsProfessor. IEEE Fellow. ELLIS Fellow. Image Processing Lab (IPL). Universitat de ValènciaVerified email at uv.es
Christian RobertUniversité Paris Dauphine, PSL & University of WarwickVerified email at ceremade.dauphine.fr
Steven Van VaerenberghAssistant professor, University of CantabriaVerified email at unican.es
Jesse ReadÉcole PolytechniqueVerified email at polytechnique.edu
Milos KrsticProfessor, University Potsdam; Team Leader, IHP, Frankfurt (Oder) GermanyVerified email at ihp-microelectronics.com
Ömer Deniz AkyildizResearch Fellow, The Alan Turing Institute and University of WarwickVerified email at warwick.ac.uk
David RamírezAssociate Professor, Universidad Carlos III de MadridVerified email at ieee.org
Yousef El-LahamStony Brook UniversityVerified email at stonybrook.edu
TianCheng LiProfessor, School of Automation, Northwestern Polytechnical UniversityVerified email at usal.es
Hongqi FanAssociate Professor of Information and Communication EngineeringVerified email at ieee.org
Mateu SbertUniversity of GironaVerified email at udg.edu
Laszlo Szirmay-KalosProfessor of Computer Science, Budapest University of Technology and EconomicsVerified email at iit.bme.hu
Mario HuemerProfessor of Signal Processing, Johannes Kepler University LinzVerified email at ieee.org

Víctor Elvira

Reader (Associate Professor), University of Edinburgh

Verified email at ed.ac.uk - Homepage

Bayesian inference computational statistics Monte Carlo methods statistical signal processing Machine Learning


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Cooperative parallel particle filters for online model selection and applications to urban mobility L Martino, J Read, V Elvira, F Louzada Digital Signal Processing 60, 172-185, 2017	96	2017
Effective sample size for importance sampling based on discrepancy measures L Martino, V Elvira, F Louzada Signal Processing 131, 386-401, 2017	91	2017
Generalized multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo Statistical Science 34 (1), 129-155, 2019	85	2019
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	83	2017
Layered adaptive importance sampling L Martino, V Elvira, D Luengo, J Corander Statistics and Computing 27 (3), 599-623, 2017	78	2017
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	69	2015
Efficient multiple importance sampling estimators V Elvira, L Martino, D Luengo, MF Bugallo IEEE Signal Processing Letters 22 (10), 1757-1761, 2015	66	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	64	2016
Improving population Monte Carlo: Alternative weighting and resampling schemes V Elvira, L Martino, D Luengo, MF Bugallo Signal Processing 131, 77-91, 2017	58	2017
Group Importance Sampling for particle filtering and MCMC L Martino, V Elvira, G Camps-Valls Digital Signal Processing 82, 133-151, 2018	51	2018
Accelerating MCMC algorithms CP Robert, V Elvira, N Tawn, C Wu Wiley Interdisciplinary Reviews: Computational Statistics 10 (5), e1435, 2018	48	2018
A general criterion for analog Tx-Rx beamforming under OFDM transmissions J Vía, I Santamaría, V Elvira, R Eickhoff IEEE Transactions on Signal Processing 58 (4), 2155-2167, 2010	47	2010
Heretical multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo IEEE Signal Processing Letters 23 (10), 1474-1478, 2016	42	2016
Adapting the number of particles in sequential Monte Carlo methods through an online scheme for convergence assessment V Elvira, J Míguez, PM Djurić IEEE Transactions on Signal Processing 65 (7), 1781-1794, 2016	41	2016
Minimum BER beamforming in the RF domain for OFDM transmissions and linear receivers J Vía, V Elvira, I Santamaria, R Eickhoff 2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009	33	2009
Optimal MIMO transmission schemes with adaptive antenna combining in the RF path I Santamaría, V Elvira, J Vía, D Ramírez, J Pérez, J Ibáñez, R Eickoff, ... 2008 16th European Signal Processing Conference, 1-5, 2008	33	2008
Weighting a resampled particle in Sequential Monte Carlo L Martino, V Elvira, F Louzada 2016 IEEE Statistical Signal Processing Workshop (SSP), 1-5, 2016	28	2016
Analog antenna combining for maximum capacity under OFDM transmissions J Vía, V Elvira, I Santamaria, R Eickhoff 2009 IEEE International Conference on Communications, 1-5, 2009	26	2009
The recycling Gibbs sampler for efficient learning L Martino, V Elvira, G Camps-Valls Digital Signal Processing 74, 1-13, 2018	24	2018
An adaptive population importance sampler L Martino, V Elvira, D Luengo, J Corander 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014	21	2014

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