 | 2011 |
| 12 |  | José Miguel Hernández-Lobato,
Pablo Morales-Mombiela,
Alberto Suárez:
Gaussianity Measures for Detecting the Direction of Causal Time Series.
IJCAI 2011: 1318-1323 |
| 11 |  | Daniel Hernández-Lobato,
José Miguel Hernández-Lobato,
Pierre Dupont:
Robust Multi-Class Gaussian Process Classification.
NIPS 2011: 280-288 |
| 10 |  | José Miguel Hernández-Lobato,
Alberto Suárez:
Semiparametric bivariate Archimedean copulas.
Computational Statistics & Data Analysis 55(6): 2038-2058 (2011) |
| 9 |  | José Miguel Hernández-Lobato,
Daniel Hernández-Lobato,
Alberto Suárez:
Network-based sparse Bayesian classification.
Pattern Recognition 44(4): 886-900 (2011) |
| 2010 |
| 8 |  | José Miguel Hernández-Lobato,
Tjeerd Dijkstra:
Hub Gene Selection Methods for the Reconstruction of Transcription Networks.
ECML/PKDD (1) 2010: 506-521 |
| 7 |  | Daniel Hernández-Lobato,
José Miguel Hernández-Lobato,
Thibault Helleputte,
Pierre Dupont:
Expectation Propagation for Bayesian Multi-task Feature Selection.
ECML/PKDD (1) 2010: 522-537 |
| 6 |  | Daniel Hernández-Lobato,
José Miguel Hernández-Lobato,
Alberto Suárez:
Expectation Propagation for microarray data classification.
Pattern Recognition Letters 31(12): 1618-1626 (2010) |
| 2008 |
| 5 |  | Daniel Hernández-Lobato,
José Miguel Hernández-Lobato:
Bayes Machines for binary classification.
Pattern Recognition Letters 29(10): 1466-1473 (2008) |
| 2007 |
| 4 |  | José Miguel Hernández-Lobato,
Daniel Hernández-Lobato,
Alberto Suárez:
GARCH Processes with Non-parametric Innovations for Market Risk Estimation.
ICANN (2) 2007: 718-727 |
| 3 |  | José Miguel Hernández-Lobato,
Tjeerd Dijkstra,
Tom Heskes:
Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach.
NIPS 2007 |
| 2006 |
| 2 |  | José Miguel Hernández-Lobato,
Alberto Suárez:
Competitive and Collaborative Mixtures of Experts for Financial Risk Analysis.
ICANN (2) 2006: 691-700 |
| 1 |  | Daniel Hernández-Lobato,
José Miguel Hernández-Lobato,
Rubén Ruiz-Torrubiano,
Ángel Valle:
Pruning Adaptive Boosting Ensembles by Means of a Genetic Algorithm.
IDEAL 2006: 322-329 |