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Víctor Elvira
Víctor Elvira
다른 이름Victor Elvira
Professor in Statistics and Data Science, University of Edinburgh
ed.ac.uk의 이메일 확인됨 - 홈페이지
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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
2952017
Effective sample size for importance sampling based on discrepancy measures
L Martino, V Elvira, F Louzada
Signal Processing 131, 386-401, 2017
2362017
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
2302020
Generalized multiple importance sampling
V Elvira, L Martino, D Luengo, MF Bugallo
Statistical Science 34 (1), 129-155, 2019
2042019
Accelerating MCMC algorithms
CP Robert, V Elvira, N Tawn, C Wu
Wiley Interdisciplinary Reviews: Computational Statistics 10 (5), e1435, 2018
1802018
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
1592017
Layered adaptive importance sampling
L Martino, V Elvira, D Luengo, J Corander
Statistics and Computing 27, 599-623, 2017
1402017
Improving population Monte Carlo: Alternative weighting and resampling schemes
V Elvira, L Martino, D Luengo, MF Bugallo
Signal Processing 131, 77-91, 2017
1102017
Blind Kalman filtering for short-term load forecasting
S Sharma, A Majumdar, V Elvira, E Chouzenoux
IEEE Transactions on Power Systems 35 (6), 4916-4919, 2020
1032020
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
1012016
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
1012015
Efficient multiple importance sampling estimators
V Elvira, L Martino, D Luengo, MF Bugallo
IEEE Signal Processing Letters 22 (10), 1757-1761, 2015
1002015
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
912016
Rethinking the effective sample size
V Elvira, L Martino, CP Robert
International Statistical Review 90 (3), 525-550, 2022
872022
Group importance sampling for particle filtering and MCMC
L Martino, V Elvira, G Camps-Valls
Digital Signal Processing 82, 133-151, 2018
782018
Simulated annealing: A review and a new scheme
T Guilmeau, E Chouzenoux, V Elvira
2021 IEEE statistical signal processing workshop (SSP), 101-105, 2021
772021
Advances in Importance Sampling
V Elvira, L Martino
Wiley StatsRef: Statistics Reference Online, 1-14, 2021
762021
Local-diffusion-based distributed SMC-PHD filtering using sensors with limited sensing range
T Li, V Elvira, H Fan, JM Corchado
IEEE Sensors Journal 19 (4), 1580-1589, 2018
672018
A general criterion for analog Tx-Rx beamforming under OFDM transmissions
J Via, I Santamaria, V Elvira, R Eickhoff
IEEE Transactions on Signal Processing 58 (4), 2155-2167, 2010
592010
Heretical multiple importance sampling
V Elvira, L Martino, D Luengo, MF Bugallo
IEEE Signal Processing Letters 23 (10), 1474-1478, 2016
572016
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