Active Bibliography

155 Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables – David Maxwell Chickering, David Heckerman - 1997
27 Learning Probabilistic Networks – Paul J Krause - 1998
155 Probabilistic independence networks for hidden Markov probability models – Padhraic Smyth, David Heckerman, Michael I. Jordan - 1997
64 A Bayesian Approach to Causal Discovery – David Heckerman, Christopher Meek, Gregory Cooper - 1997
7 Population Markov Chain Monte Carlo – Kathryn Blackmond Laskey, James Myers - 2003
6 Exploiting parameter domain knowledge for learning in Bayesian networks – Radu Stefan Niculescu - 2005
Modeling the Impact of Organizational Change: A Bayesian Network Approach – Ronald D. Anderson, R. Thomas Lenz - 2001
A guide to the literature on learning probabilistic . . . – Wray Buntine
156 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
16 Learning with Mixtures of Trees – Marina Meila-Predoviciu - 1999
102 Machine-Learning Research -- Four Current Directions – Thomas G. Dietterich
7 Prior Information and Generalized Questions – Jörg C. Lemm - 1996
5 Bayesian Networks with Applications in Reliability Analysis – Helge Langseth - 2002
2 Stochastic Complexity Based Estimation of Missing Elements in Questionnaire Data – Henry Tirri, Tomi Silander - 1998
393 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
8 Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains – Helge Langseth, Thomas D. Nielsen, Richard Dybowski - 2003
Just Enough Die-Level Test: Optimizing IC Test via Machine Learning and Decision Theory – Tony Fountain - 1998
35 Bayesian Model Averaging And Model Selection For Markov Equivalence Classes Of Acyclic Digraphs – David Madigan, Steen Andersson, Michael Perlman, Chris Volinsky - 1996
Bayesian AI Tutorial – Kevin B. Korb, Ann E. Nicholson