Mauricio A. Álvarez
Mauricio A. Álvarez
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Kernels for vector-valued functions: A review
MA Alvarez, L Rosasco, ND Lawrence
arXiv preprint arXiv:1106.6251, 2011
Computationally efficient convolved multiple output Gaussian processes
MA Alvarez, ND Lawrence
The Journal of Machine Learning Research 12, 1459-1500, 2011
Sparse convolved Gaussian processes for multi-output regression
M Alvarez, N Lawrence
Latent force models
M Alvarez, D Luengo, ND Lawrence
Artificial Intelligence and Statistics, 9-16, 2009
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
Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison
CD Zuluaga, MA Alvarez, E Giraldo
Applied Energy 156, 321-330, 2015
Linear latent force models using Gaussian processes
MA Alvarez, D Luengo, ND Lawrence
IEEE transactions on pattern analysis and machine intelligence 35 (11), 2693 …, 2013
Heterogeneous multi-output gaussian process prediction
P Moreno-Muńoz, A Artés-Rodríguez, MA Álvarez
arXiv preprint arXiv:1805.07633, 2018
Switched latent force models for movement segmentation
M Alvarez, J Peters, N Lawrence, B Schölkopf
Advances in neural information processing systems 23, 55-63, 2010
Comparative analysis of physiological signals and electroencephalogram (EEG) for multimodal emotion recognition using generative models
CA Torres-Valencia, HF Garcia-Arias, MAA Lopez, AA Orozco-Gutiérrez
2014 XIX Symposium on Image, Signal Processing and Artificial Vision, 1-5, 2014
SVM-based feature selection methods for emotion recognition from multimodal data
C Torres-Valencia, M Álvarez-López, Á Orozco-Gutiérrez
Journal on Multimodal User Interfaces 11 (1), 9-23, 2017
Feature selection for multimodal emotion recognition in the arousal-valence space
CA Torres, ÁA Orozco, MA Álvarez
2013 35th Annual International Conference of the IEEE Engineering in …, 2013
Efficient modeling of latent information in supervised learning using gaussian processes
Z Dai, MA Álvarez, ND Lawrence
arXiv preprint arXiv:1705.09862, 2017
Gaussian process latent force models for learning and stochastic control of physical systems
S Särkkä, MA Alvarez, ND Lawrence
IEEE Transactions on Automatic Control 64 (7), 2953-2960, 2018
Differentially private regression with gaussian processes
M Smith, M Álvarez, M Zwiessele, ND Lawrence
International Conference on Artificial Intelligence and Statistics, 1195-1203, 2018
Gaussian process dynamical models for multimodal affect recognition
HF García, MA Álvarez, ÁÁ Orozco
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
Multi-task learning for aggregated data using Gaussian processes
F Yousefi, MT Smith, MA Álvarez
arXiv preprint arXiv:1906.09412, 2019
Convolved Gaussian process priors for multivariate regression with applications to dynamical systems
MA Alvarez
PQDT-UK & Ireland, 2011
Non-linear process convolutions for multi-output Gaussian processes
MA Álvarez, W Ward, C Guarnizo
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Fast kernel approximations for latent force models and convolved multiple-output Gaussian processes
C Guarnizo, MA Álvarez
arXiv preprint arXiv:1805.07460, 2018
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