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» Modelling Variability for System Families
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UAI
2004
13 years 10 months ago
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Peter Hooper
JMLR
2006
103views more  JMLR 2006»
13 years 8 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev
RTAS
2007
IEEE
14 years 3 months ago
Stochastic Metrics for Debugging the Timing Behaviour of Real-Time Systems
Stochastic analysis techniques for real-time systems model the execution time of tasks as random variables. These techniques constitute a very powerful tool to study the behaviour...
Joaquín Entrialgo, Javier García, Jo...
HICSS
2007
IEEE
174views Biometrics» more  HICSS 2007»
14 years 3 months ago
A Comparison of Statistical Approaches for Genetic Anticipation with Application to Pancreatic Cancer
Genetic anticipation for a particular disease can involve an earlier age at onset (or, diagnosis), greater severity, and/or a higher number of affected individuals in successive g...
Gleb R. Haynatzki, Randall E. Brand, Vera R. Hayna...
WSC
1998
13 years 10 months ago
Multimodels and Dynamic Structure Models: An Integration of DSDE/DEVS and OOPM
Constructing models of systems that change their structure over time has proved to be a challenging problem, with several proposed solutions. We present two of these approaches an...
Fernando J. Barros, Bernard P. Zeigler, Paul A. Fi...