A Tutorial on Learning Bayesian Networks (1995)

by David Heckerman
Venue:Communications of the ACM
Citations:299 - 13 self

Active Bibliography

913 Learning Bayesian networks: The combination of knowledge and statistical data – David Heckerman, David M. Chickering - 1995
unknown title – Learning Bayesian
36 Learning Probabilistic Networks – Paul J Krause - 1998
274 Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains – David Beckerman, Dan Geiger
58 A Bayesian approach to learning causal networks – David Heckerman - 1995
849 A tutorial on learning with Bayesian networks – David Heckerman - 1995
31 A characterization of the Dirichlet distribution through global and local parameter independence, The Annals of Statistics – Author(s) Dan Geiger, David Heckerman, Geiger, David Heckerman - 1997
26 Parameter priors for directed acyclic graphical models and the characterization of several probability distributions – Dan Geiger, David Heckerman - 1999
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
24 A characterization of the Dirichlet distribution with application to learning Bayesian networks – Dan Geiger, David Heckerman - 1995
CONTENTS Causal Networks Learning Acausal Networks Learning Influence Diagrams Learning Causal-Network Parameters Learning Causal-Network Structure – David Heckerman
216 Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions – Dan Geiger, David Heckerman
23 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
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
249 Operations for Learning with Graphical Models – Wray L. Buntine - 1994
45 Learning Bayesian Networks: A unification for discrete and Gaussian domains – David Heckerman, Dan Geiger - 1995
21 Graphical Models for Probabilistic and Causal reasoning – Judea Pearl - 2004
130 Learning Bayesian Networks is NP-Hard – David Chickering, Dan Geiger, David Heckerman - 1994