VIBES: A Variational Inference Engine for Bayesian Networks

NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Volumn , Issue , 2002, Pages 777-784

  Bishop, Christopher M ^a   Spiegelhalter, David ^b   Winn, John ^c  

^a MICROSOFT RESEARCH   (United Kingdom)

^b MRC BIOSTATISTICS UNIT   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ENGINES; INFERENCE ENGINES; VARIATIONAL TECHNIQUES;

APPLICATION-SPECIFIC CODES; APPROXIMATE INFERENCE; BAYESIA N NETWORKS; ERROR PRONES; NEW APPLICATIONS; PROBABILISTIC MODELS; SIMPLE++; VARIATIONAL INFERENCE; VARIATIONAL METHODS; VARIATIONAL UPDATES;

BAYESIAN NETWORKS;

EID: 85156251109     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul. An introduction to variational methods for graphical models. In M. I. Jordan, editor, Learning in Graphical Models, pages 105-162. Kluwer, 1998.
2. R. M. Neal and G. E. Hinton. A new view of the EM algorithm that justifies incremental and other variants. In M. I. Jordan, editor, Learning in Graphical Models, pages 355-368. Kluwer, 1998.
3. D J Lunn, A Thomas, N G Best, and D J Spiegelhalter. WinBUGS - a Bayesian modelling framework: concepts, structure and extensibility. Statistics and Computing, 10:321-333, 2000. http://www.mrc-bsu.cam.ac.uk/bugs/.
4. Z. Ghahramani and M. J. Beal. Propagation algorithms for variational Bayesian learning. In T. K. Leen, T. Dietterich, and V. Tresp, editors, Advances in Neural Information Processing Systems, volume 13, Cambridge MA, 2001. MIT Press.
5. H. Attias. A variational Bayesian framework for graphical models. In S. Solla, T. K. Leen, and K-L Muller, editors, Advances in Neural Information Processing Systems, volume 12, pages 209-215, Cambridge MA, 2000. MIT Press.
6. C. M. Bishop. Variational principal components. In Proceedings Ninth International Conference on Artificial Neural Networks, ICANN'99, volume 1, pages 509-514. IEE, 1999.
7. Christopher M. Bishop and John Winn. Structured variational distributions in VIBES. In Proceedings Artificial Intelligence and Statistics, Key West, Florida, 2003. Accepted for publication.