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All publications by Ricardo Silva
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Causal Inference through a Witness Protection Program
Ricardo Silva and Robin Evans
Advances in Neural Information Processing Systems 27, 2014


Flexible sampling of discrete data correlations without the marginal distributions
Alfredo Kalaitzis and Ricardo Silva
Advances in Neural Information Processing Systems 26, 2013


Thinning Measurement Models and Questionnaire Design
Ricardo Silva
Advances in Neural Information Processing Systems 24, 2011


Discussion of "Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables"
Jiji Zhang and Ricardo Silva
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Mixed Cumulative Distribution Networks
Ricardo Silva, Charles Blundell and Yee W. Teh
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models
Ricardo Silva and Zoubin Ghahramani
Journal of Machine Learning Research, 2009


Factorial Mixture of Gaussians and the Marginal Independence Model
Ricardo Silva and Zoubin Ghahramani
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


MCMC Methods for Bayesian Mixtures of Copulas
Ricardo Silva and Robert B. Gramacy
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Hidden Common Cause Relations in Relational Learning
Ricardo Silva, Wei Chu and Zoubin Ghahramani
Advances in Neural Information Processing Systems 20, 2007


Analogical Reasoning with Relational Bayesian Sets
Ricardo Silva, Katherine A. Heller and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Bayesian learning of measurement and structural models
Ricardo Silva and Richard Scheines
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Learning the Structure of Linear Latent Variable Models
Ricardo Silva, Richard Scheines, Clark Glymour and Peter Spirtes
Journal of Machine Learning Research, 2006


New d-separation identification results for learning continuous latent variable models
Ricardo Silva and Richard Scheines
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005