Graphical Models for Discovering Knowledge (1995)

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by Wray Buntine
Citations:28 - 2 self

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247 Operations for Learning with Graphical Models – Wray L. Buntine - 1994
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
1 Software for Data Analysis With Graphical Models – Wray Buntine, H. Scott Roy - 1995
MLnet Summer School on Machine Learning and Knowledge Acquisition: LEARNING AND PROBABILITIES – Wray Buntine
28 Chain Graphs for Learning – Wray Buntine - 1995
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
36 Learning Probabilistic Networks – Paul J Krause - 1998
1 Divide and Conquer: Pattern Recognition using Mixtures of Experts – Steve Waterhouse, Steve Waterhouse - 1997
854 A tutorial on learning with Bayesian networks – David Heckerman - 1995
21 Graphical Models for Probabilistic and Causal reasoning – Judea Pearl - 2004
58 A Bayesian approach to learning causal networks – David Heckerman - 1995
Just Enough Die-Level Test: Optimizing IC Test via Machine Learning and Decision Theory – Tony Fountain - 1998
32 Planning and control in stochastic domains with imperfect information – Milos Hauskrecht - 1997
26 Parameter priors for directed acyclic graphical models and the characterization of several probability distributions – Dan Geiger, David Heckerman - 1999
23 Likelihoods and Parameter Priors for Bayesian Networks – David Heckerman, Dan Geiger - 1995
25 Inference and Learning in Hybrid Bayesian Networks – Kevin P. Murphy - 1998
2 Outlier management in intelligent data analysis – J. Gongxian Cheng - 2000
25 Learning mixtures of DAG models – Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman - 1997
9 Computationally efficient methods for selecting among mixtures of graphical models – B. Thiesson, C. Meek, D. M. Chickering, D. Heckerman - 1999