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 | 258 | 2017 |
Effective sample size for importance sampling based on discrepancy measures L Martino, V Elvira, F Louzada Signal Processing 131, 386-401, 2017 | 214 | 2017 |
Generalized multiple importance sampling V Elvira, L Martino, D Luengo, MF Bugallo | 187 | 2019 |
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 | 179 | 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 | 152 | 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 | 138 | 2014 |
Layered adaptive importance sampling L Martino, V Elvira, D Luengo, J Corander Statistics and Computing, 1-25, 2015 | 135 | 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 | 130* | 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 | 108 | 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 | 108* | 2014 |
A review of multiple try MCMC algorithms for signal processing L Martino Digital Signal Processing 75, 134-152, 2018 | 104 | 2018 |
Improving population Monte Carlo: Alternative weighting and resampling schemes V Elvira, L Martino, D Luengo, MF Bugallo Signal Processing 131, 77-91, 2017 | 103 | 2017 |
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 |
Independent random sampling methods L Martino, D Luengo, J Míguez Springer International Publishing, 2018 | 91 | 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 | 89 | 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 | 86 | 2018 |
Adaptive importance sampling in signal processing MF Bugallo, L Martino, J Corander Digital Signal Processing 47, 36-49, 2015 | 79 | 2015 |
Rethinking the effective sample size V Elvira, L Martino, CP Robert International Statistical Review 90 (3), 525-550, 2022 | 76 | 2022 |
Group importance sampling for particle filtering and MCMC L Martino, V Elvira, G Camps-Valls Digital Signal Processing 82, 133-151, 2018 | 75 | 2018 |