Luca Martino
Luca Martino
Associate Professor
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Geciteerd door
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
Effective sample size for importance sampling based on discrepancy measures
L Martino, V Elvira, F Louzada
Signal Processing 131, 386-401, 2017
Generalized multiple importance sampling
V Elvira, L Martino, D Luengo, MF Bugallo
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
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
Efficient monte carlo methods for multi-dimensional learning with classifier chains
J Read, L Martino, D Luengo
Pattern Recognition 47 (3), 1535-1546, 2014
Layered adaptive importance sampling
L Martino, V Elvira, D Luengo, J Corander
Statistics and Computing, 1-25, 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
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
Orthogonal MCMC algorithms
L Martino, V Elvira, D Luengo, A Artes-Rodriguez, J Corander
2014 IEEE Workshop on Statistical Signal Processing (SSP), 364-367, 2014
A review of multiple try MCMC algorithms for signal processing
L Martino
Digital Signal Processing 75, 134-152, 2018
Improving population Monte Carlo: Alternative weighting and resampling schemes
V Elvira, L Martino, D Luengo, MF Bugallo
Signal Processing 131, 77-91, 2017
Efficient multiple importance sampling estimators
V Elvira, L Martino, D Luengo, MF Bugallo
IEEE Signal Processing Letters 22 (10), 1757-1761, 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
Independent random sampling methods
L Martino, D Luengo, J Míguez
Springer International Publishing, 2018
Marginal likelihood computation for model selection and hypothesis testing: an extensive review
F Llorente, L Martino, D Delgado, J Lopez-Santiago
SIAM review 65 (1), 3-58, 2023
Physics-aware Gaussian processes in remote sensing
G Camps-Valls, L Martino, DH Svendsen, M Campos-Taberner, ...
Applied Soft Computing 68, 69-82, 2018
Adaptive importance sampling in signal processing
MF Bugallo, L Martino, J Corander
Digital Signal Processing 47, 36-49, 2015
Rethinking the effective sample size
V Elvira, L Martino, CP Robert
International Statistical Review 90 (3), 525-550, 2022
Group importance sampling for particle filtering and MCMC
L Martino, V Elvira, G Camps-Valls
Digital Signal Processing 82, 133-151, 2018
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