36

Learning Probabilistic Networks
– Paul J Krause
 1998

79

A Bayesian Approach to Causal Discovery
– David Heckerman, Christopher Meek, Gregory Cooper
 1997

849

A tutorial on learning with Bayesian networks
– David Heckerman
 1995

3

A Bayesian Local Causal Discovery Framework
– Subramani Mani
 2005

8

Challenge: Where is the Impact of Bayesian Networks in Learning?
– Nir Friedman, Moises Goldszmidt, David Heckerman
 1997

2

Bayesian Networks for Genomic Analysis
– Paola Sebastiani, Maria M. Abad, Marco F. Ramoni
 2004

10

Causal Inference
– Peter Spirtes, Richard Scheines, Clark Glymour, Thomas Richardson, Christopher Meek

28

Causal Inference in the Presence of Latent Variables and Selection Bias
– Peter Spirtes, Christopher Meek, Thomas Richardson


unknown title
– Learning Bayesian

2

Information Fusion, Causal Probabilistic Network And Probanet II: Inference Algorithms and Probanet System
– Heping Pan, Daniel McMichael, Marta Lendjel
 1997

172

A Guide to the Literature on Learning Probabilistic Networks From Data
– Wray Buntine
 1996

7

Finding Optimal Bayesian Network Given a SuperStructure
– Eric Perrier, Seiya Imoto, Satoru Miyano, Max Chickering

23

Likelihoods and Parameter Priors for Bayesian Networks
– David Heckerman, Dan Geiger
 1995


CONTENTS Causal Networks Learning Acausal Networks Learning Influence Diagrams Learning CausalNetwork Parameters Learning CausalNetwork Structure
– David Heckerman

58

A Bayesian approach to learning causal networks
– David Heckerman
 1995

2

Modeling the Impact of Organizational Change: A Bayesian Network Approach
– Ronald D. Anderson, R. Thomas Lenz
 2001

114

MachineLearning Research  Four Current Directions
– Thomas G. Dietterich

564

Dynamic Bayesian Networks: Representation, Inference and Learning
– Kevin Patrick Murphy
 2002

17

A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests
– Luis M. de Campos
 2006
