Results 21 to 30 of about 207,453 (329)
Relational Dynamic Bayesian Networks
Journal of Artificial Intelligence Research, 2005 Stochastic processes that involve the creation of objects and relations over time are widespread, but relatively poorly studied. For example, accurate fault diagnosis in factory assembly processes requires inferring the probabilities of erroneous assembly operations, but doing this efficiently and accurately is difficult.
Sanghai, S., Domingos, P., Weld, D.
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Probabilistic Prognosis with Dynamic Bayesian Networks
International Journal of Prognostics and Health Management, 2015 This paper proposes a methodology for probabilistic prognosis of a system using a dynamic Bayesian network (DBN). Dynamic Bayesian networks are suitable for probabilistic prognosis because of their ability to integrate information in a variety of formats
Gregory Bartram, Sankaran Mahadevan
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Identifiability and transportability in dynamic causal networks [PDF]
, 2016 In this paper we propose a causal analog to the purely observational Dynamic Bayesian Networks, which we call Dynamic Causal Networks. We provide a sound and complete algorithm for identification of Dynamic Causal Networks, namely, for computing the ...
Arias Vicente, Marta +2 more
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Frontiers in Psychology, 2022 An overarching mission of the educational assessment community today is strengthening the connection between assessment and learning. To support this effort, researchers draw variously on developments across technology, analytic methods, assessment ...
Younyoung Choi, Robert J. Mislevy
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Dynamic Bayesian networks for meeting structuring [PDF]
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004 The paper is about the automatic structuring of multiparty meetings using audio information. We have used a corpus of 53 meetings, recorded using a microphone array and lapel microphones for each participant. The task was to segment meetings into a sequence of meeting actions, or phases.
Dielmann, Alfred, Renals, Steve
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Outlier Detection for Multivariate Time Series Using Dynamic Bayesian Networks
Applied Sciences, 2021 Outliers are observations suspected of not having been generated by the underlying process of the remaining data. Many applications require a way of identifying interesting or unusual patterns in multivariate time series (MTS), now ubiquitous in many ...
Jorge L. Serras +2 more
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Reliability analysis of dynamic systems by translating temporal fault trees into Bayesian networks [PDF]
, 2014 Classical combinatorial fault trees can be used to assess combinations of failures but are unable to capture sequences of faults, which are important in complex dynamic systems.
A. Bobbio +9 more
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Exact Inference Techniques for the Analysis of Bayesian Attack Graphs [PDF]
, 2016 Attack graphs are a powerful tool for security risk assessment by analysing network vulnerabilities and the paths attackers can use to compromise network resources.
Barrère, Martín +3 more
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Dynamic Bayesian inference method for structural fatigue crack propagation based on particle filter
Hangkong gongcheng jinzhan, 2023 Accurately predicting the fatigue crack propagation process of aircraft structure is the basis for conducting life monitoring and residual life estimation of individual aircraft.
QI Xin +4 more
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Applied Sciences, 2023 Urban roads face significant challenges from the unpredictable and destructive characteristics of natural or man-made disasters, emphasizing the importance of modeling and evaluating their resilience for emergency management. Resilience is the ability to
Gang Yu +3 more
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