A Tutorial on Learning Bayesian Networks (1995)

by David Heckerman
Venue:Communications of the ACM
Citations:248 - 11 self

Active Bibliography

752 Learning Bayesian networks: The combination of knowledge and statistical data – David Heckerman, David M. Chickering - 1995
52 A Bayesian approach to learning causal networks – David Heckerman - 1995
27 Learning Probabilistic Networks – Paul J Krause - 1998
23 Parameter priors for directed acyclic graphical models and the characterization of several probability distributions – Dan Geiger, David Heckerman - 1999
710 A tutorial on learning with Bayesian networks – David Heckerman - 1995
393 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
53 Causal independence for probability assessment and inference using Bayesian networks – David Heckerman, John S. Breese - 1994
24 A Characterization of the Dirichlet Distribution through Global and Local Independence – Dan Geiger, David Heckerman - 1995
18 A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks – Dan Geiger, David Heckerman - 1995
20 Likelihoods and Parameter Priors for Bayesian Networks – David Heckerman, Dan Geiger - 1995
1 Software for Data Analysis With Graphical Models – Wray Buntine, H. Scott Roy - 1995
156 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
214 Operations for Learning with Graphical Models – Wray L. Buntine - 1994
36 Learning Bayesian Networks: A unification for discrete and Gaussian domains – David Heckerman, Dan Geiger - 1995
17 Learning Causal Networks from Data: A survey and a new algorithm for recovering possibilistic causal networks – Ramon Sangüesa, Ulises Cortés - 1997
98 Learning Bayesian Networks is NP-Hard – David Chickering, Dan Geiger, David Heckerman - 1994
64 A Bayesian Approach to Causal Discovery – David Heckerman, Christopher Meek, Gregory Cooper - 1997
A guide to the literature on learning probabilistic . . . – Wray Buntine
155 Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables – David Maxwell Chickering, David Heckerman - 1997