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    BIOCOMP
    2006
    233views Bioinformatics» more  BIOCOMP 2006»
    Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
    13 years 8 months ago
    Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
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    Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
    Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
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    UAI
    1996
    135views Artificial Intelligence» more  UAI 1996»
    Asymptotic Model Selection for Directed Networks with Hidden Variables
    13 years 8 months ago
    Asymptotic Model Selection for Directed Networks with Hidden Variables
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    We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
    Dan Geiger, David Heckerman, Christopher Meek
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    IJAR
    2006
    89views more  IJAR 2006»
    Learning probabilistic decision graphs
    13 years 6 months ago
    Learning probabilistic decision graphs
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    Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
    Manfred Jaeger, Jens D. Nielsen, Tomi Silander
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    SUM
    2009
    Springer
    131views Information Technology» more  SUM 2009»
    Modeling Unreliable Observations in Bayesian Networks by Credal Networks
    14 years 1 months ago
    Modeling Unreliable Observations in Bayesian Networks by Credal Networks
    Download  www.idsia.ch
    Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
    Alessandro Antonucci, Alberto Piatti
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    EDM
    2010
    165views Data Mining» more  EDM 2010»
    Using a Bayesian Knowledge Base for Hint Selection on Domain Specific Problems
    13 years 8 months ago
    Using a Bayesian Knowledge Base for Hint Selection on Domain Specific Problems
    Download  educationaldatamining.org
    A Bayesian Knowledge Base is a generalization of traditional Bayesian Networks where nodes or groups of nodes have independence. In this paper we describe a method of generating a ...
    John C. Stamper, Tiffany Barnes, Marvin J. Croy
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