フォロー
David Luengo
タイトル
引用先
引用先
年
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
Latent force models
M Alvarez, D Luengo, ND Lawrence
Artificial intelligence and statistics, 9-16, 2009
2452009
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
2292020
Generalized multiple importance sampling
V Elvira, L Martino, D Luengo, MF Bugallo
2042019
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
1612010
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
1512013
Efficient monte carlo methods for multi-dimensional learning with classifier chains
J Read, L Martino, D Luengo
Pattern Recognition 47 (3), 1535-1546, 2014
1422014
Layered adaptive importance sampling
L Martino, V Elvira, D Luengo, J Corander
Statistics and Computing 27, 599-623, 2017
1402017
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
1152015
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
1142015
Improving population Monte Carlo: Alternative weighting and resampling schemes
V Elvira, L Martino, D Luengo, MF Bugallo
Signal Processing 131, 77-91, 2017
1102017
Independent random sampling methods
L Martino, D Luengo, J Míguez
Springer International Publishing, 2018
1062018
Physics-aware Gaussian processes in remote sensing
G Camps-Valls, L Martino, DH Svendsen, M Campos-Taberner, ...
Applied Soft Computing 68, 69-82, 2018
1012018
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
Feature extraction of galvanic skin responses by nonnegative sparse deconvolution
F Hernando-Gallego, D Luengo, A Artés-Rodríguez
IEEE journal of biomedical and health informatics 22 (5), 1385-1394, 2017
782017
Heretical multiple importance sampling
V Elvira, L Martino, D Luengo, MF Bugallo
IEEE Signal Processing Letters 23 (10), 1474-1478, 2016
572016
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
572013
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
512015
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