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» Importance Sampling for Continuous Time Bayesian Networks
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JAIR
2010
181views more  JAIR 2010»
13 years 4 months ago
Intrusion Detection using Continuous Time Bayesian Networks
Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems (NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor sys...
Jing Xu, Christian R. Shelton
ICML
2010
IEEE
13 years 8 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier
BMCBI
2007
164views more  BMCBI 2007»
13 years 9 months ago
Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...
ICASSP
2008
IEEE
14 years 4 months ago
A new Particle Filtering algorithm with structurally optimal importance function
Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
Boujemaa Ait-El-Fquih, François Desbouvries
IJAR
2006
80views more  IJAR 2006»
13 years 9 months ago
Operations for inference in continuous Bayesian networks with linear deterministic variables
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...
Barry R. Cobb, Prakash P. Shenoy