Active Bibliography

22 Bayesian models of cognition – Thomas L. Griffiths, Charles Kemp, Joshua B. Tenenbaum
563 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
Bayesian Modelling in Machine Learning: A Tutorial Review – Matthias Seeger - 2009
25 Language Evolution by Iterated Learning With Bayesian Agents – Thomas L. Griffiths , Michael L. Kalish - 2007
6 Bayesian Input Variable Selection Using Posterior Probabilities and Expected Utilities – Aki Vehtari, Jouko Lampinen - 2002
1 A tutorial introduction to Bayesian models of cognitive development – Amy Perfors, Joshua B. Tenenbaum, Thomas L. Griffiths, Fei Xu
12 Population Markov Chain Monte Carlo – Kathryn Blackmond Laskey, James Myers - 2003
11 Machine Learning Based on Attribute Interactions – Aleks Jakulin - 2005
7 Natively probabilistic computing – Vikash Kumar Mansinghka, Joshua B. Tenenbaum - 2009
19 Unsupervised learning – Zoubin Ghahramani - 2004
2 Machine Learning: A Probabilistic Approach – David Barber - 2006
9 Exploiting parameter domain knowledge for learning in Bayesian networks – Radu Stefan Niculescu - 2005
18 Super Resolution of Images and Video – Aggelos K. Katsaggelos, Rafael Molina, Javier Mateos
31 An Introduction to Graphical Models – Kevin P. Murphy - 2001
2 Graphical Models: Parameter Learning – Zoubin Ghahramani - 2003
Proposed design for gR, a graphical models toolkit for R – Kevin P. Murphy - 2003
36 Learning Probabilistic Networks – Paul J Krause - 1998
Just Enough Die-Level Test: Optimizing IC Test via Machine Learning and Decision Theory – Tony Fountain - 1998
175 Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables – David Maxwell Chickering, David Heckerman - 1997