Causal Inference in the Presence of Latent Variables and Selection Bias (0)

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by Peter Spirtes , Christopher Meek , Thomas Richardson
Venue:In Proceedings of Eleventh Conference on Uncertainty in Artificial Intelligence
Citations:28 - 4 self

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93 Learning Bayesian Networks from Data: An Information-Theory Based Approach – Jie Cheng, Russell Greiner, Jonathan Kelly, David Bell, Weiru Liu
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
37 Improved learning of Bayesian networks – Robert Castelo, Craig Boutilier - 2001
12 The TETRAD Project: Constraint Based Aids to Causal Model Specification – Richard Scheines , Peter Spirtes, Clark Glymour, Christopher Meek, Thomas Richardson
3 Towards an inclusion driven learning of Bayesian Networks – Robert Castelo, Tomas Kocka - 2002
17 A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests – Luis M. de Campos - 2006
2 LEARNING THE STRUCTURE OF BAYESIAN NETWORKS WITH CONSTRAINT SATISFACTION – Andrew S. Fast - 2010
44 Graphs, Causality, And Structural Equation Models – Judea Pearl - 1998
79 A Bayesian Approach to Causal Discovery – David Heckerman, Christopher Meek, Gregory Cooper - 1997
29 Using Path Diagrams as a Structural Equation Modelling Tool – Peter Spirtes, Thomas Richardson, Chris Meek, Richard Scheines, Clark Glymour - 1997
4 A Parallel Learning Algorithm for Bayesian Inference Networks – Wai Lam, Alberto Maria Segre
76 The max-min hill-climbing bayesian network structure learning algorithm – Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis - 2006
10 Causal Inference – Peter Spirtes, Richard Scheines, Clark Glymour, Thomas Richardson, Christopher Meek
unknown title – Learning Bayesian
849 A tutorial on learning with Bayesian networks – David Heckerman - 1995
913 Learning Bayesian networks: The combination of knowledge and statistical data – David Heckerman, David M. Chickering - 1995
19 Learning Causal Networks from Data: A survey and a new algorithm for recovering possibilistic causal networks – Ramon Sangüesa, Ulises Cortés - 1997
3 A Bayesian Local Causal Discovery Framework – Subramani Mani - 2005
27 A new approach for learning belief networks using independence criteria – Luis M. De Campos, Juan F. Huete - 2000