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IJPRAI
1998
100views more  IJPRAI 1998»
15 years 5 months ago
Obtaining The Correspondence between Bayesian and Neural Networks
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Athena Stassopoulou, Maria Petrou
131
Voted
ISMIS
2003
Springer
15 years 10 months ago
Comparing Hierarchical Markov Networks and Multiply Sectioned Bayesian Networks
Abstract. Multiply sectioned Bayesian networks (MSBNs) were originally proposed as a modular representation of uncertain knowledge by sectioning a large Bayesian network (BN) into ...
Cory J. Butz, H. Geng
FLAIRS
2004
15 years 6 months ago
Mining Bayesian Networks to Forecast Adverse Outcomes Related to Acute Coronary Syndrome
One fascinating aspect of tool building for datamining is the application of a generalized datamining tool to a specific domain. Often times, this process results in a cross disci...
Andy Novobilski, Francis M. Fesmire, David Sonnema...
JMLR
2010
140views more  JMLR 2010»
15 years 6 days ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
ICDM
2007
IEEE
153views Data Mining» more  ICDM 2007»
15 years 11 months ago
HSN-PAM: Finding Hierarchical Probabilistic Groups from Large-Scale Networks
Real-world social networks are often hierarchical, reflecting the fact that some communities are composed of a few smaller, sub-communities. This paper describes a hierarchical B...
Haizheng Zhang, Wei Li, Xuerui Wang, C. Lee Giles,...