Inference and Learning in Hybrid Bayesian Networks (1998)

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by Kevin P. Murphy
Citations:25 - 2 self

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564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
9 Exploiting parameter domain knowledge for learning in Bayesian networks – Radu Stefan Niculescu - 2005
58 Switching Kalman Filters – Kevin P. Murphy - 1998
36 Learning Probabilistic Networks – Paul J Krause - 1998
157 Modelling gene expression data using dynamic bayesian networks – Kevin Murphy, Saira Mian - 1999
67 Graphical models and automatic speech recognition – Jeffrey A. Bilmes - 2003
2 Machine Learning: A Probabilistic Approach – David Barber - 2006
4 Logic, Knowledge Representation and Bayesian Decision Theory – David Poole - 2000
249 Operations for Learning with Graphical Models – Wray L. Buntine - 1994
2 Information Fusion, Causal Probabilistic Network And Probanet II: Inference Algorithms and Probanet System – Heping Pan, Daniel McMichael, Marta Lendjel - 1997
Graphical Models And Variational Approximation – Michael Jordan, Zoubin Ghahramani, Tommi Jaakkola, Marina Meila, Lawrence Saul - 1998
Proposed design for gR, a graphical models toolkit for R – Kevin P. Murphy - 2003
9 Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains – Helge Langseth, Thomas D. Nielsen, Richard Dybowski - 2003
45 Learning Probabilities for Noisy First-Order Rules – Daphne Koller, Avi Pfeffer - 1997
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
4 Conditioning Graphs: Practical Structures for Inference in Bayesian Networks – Kevin John Grant - 2007
Just Enough Die-Level Test: Optimizing IC Test via Machine Learning and Decision Theory – Tony Fountain - 1998
Bayesian AI Tutorial – Kevin B. Korb, Ann E. Nicholson
12 Towards Perceptual Intelligence: Statistical Modeling of Human Individual and Interactive Behaviors – Nuria M. Oliver - 1995