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Inference in Bayesian Networks Using Nested Junction Trees
Learning in Graphical Models
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10.1007/978-94-011-5014-9_3
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1998
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pp. 51-74
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Cited By ~ 3
Author(s):
Uffe Kjærulff
Keyword(s):
Bayesian Networks
◽
Junction Trees
Download Full-text
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Cited By
References
Hierarchical Junction Trees: Conditional Independence Preservation and Forecasting in Dynamic Bayesian Networks with Heterogeneous Evolution
Advances in Bayesian Networks - Studies in Fuzziness and Soft Computing
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10.1007/978-3-540-39879-0_4
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2004
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pp. 57-75
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Cited By ~ 1
Author(s):
Roberto O. Puch
◽
Jim Q. Smith
◽
Concha Bielza
Keyword(s):
Bayesian Networks
◽
Conditional Independence
◽
Dynamic Bayesian Networks
◽
Junction Trees
Download Full-text
Junction trees construction: Application to Bayesian networks
10.1063/1.5064936
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2018
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Author(s):
L. Smail
Keyword(s):
Bayesian Networks
◽
Junction Trees
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Hierarchical Junction Trees as the Secondary Structure for Inference in Bayesian Networks
Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)
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10.1109/snpd.2007.461
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2007
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Cited By ~ 1
Author(s):
Dan Wu
◽
Libing Wu
Keyword(s):
Secondary Structure
◽
Bayesian Networks
◽
Junction Trees
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Junction trees constructions in Bayesian networks
Journal of Physics Conference Series
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10.1088/1742-6596/893/1/012056
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2017
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Vol 893
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pp. 012056
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Cited By ~ 2
Author(s):
Linda Smail
Keyword(s):
Bayesian Networks
◽
Junction Trees
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Using junction trees for structural learning of Bayesian networks
Journal of Systems Engineering and Electronics
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10.1109/jsee.2012.00036
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2012
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Vol 23
(2)
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pp. 286-292
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Cited By ~ 2
Author(s):
Mingmin Zhu
◽
Sanyang Liu
◽
Youlong Yang
◽
Kui Liu
Keyword(s):
Bayesian Networks
◽
Structural Learning
◽
Junction Trees
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Investigating Nonlinearities With Bayesian Networks
PsycEXTRA Dataset
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10.1037/e340982004-001
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2003
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Author(s):
Petri Nokelainen
Keyword(s):
Bayesian Networks
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ON THE UNIVERSALITY OF BAYESIAN NETWORKS IN THE CONTEXT OF DATA INDEPENDENCE
Философия науки
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10.15372/ps20170404
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2017
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Keyword(s):
Bayesian Networks
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Data Independence
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A complex mechanical system importance calculation method based on discrete-time Bayesian networks
Recent Developments on Reliability, Maintenance and Safety
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10.2495/qr2mse140401
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2015
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Author(s):
Y. K. Gu
Keyword(s):
Bayesian Networks
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Mechanical System
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Discrete Time
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Calculation Method
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Complex Mechanical System
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Faculty Opinions recommendation of A Bayesian networks approach for predicting protein-protein interactions from genomic data.
Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature
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10.3410/f.1016965.201724
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2004
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Author(s):
Rolf Apweiler
Keyword(s):
Bayesian Networks
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Protein Interactions
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Genomic Data
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Protein Protein Interactions
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Faculty Opinions recommendation of Use of transcriptomic data to inform biophysical models via Bayesian networks.
Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature
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10.3410/f.738632599.793578292
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2020
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Author(s):
Bertrand Muller
Keyword(s):
Bayesian Networks
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Transcriptomic Data
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Biophysical Models
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