Results 1 to 10 of about 394,931 (262)
CausNet-partial: 'Partial Generational Orderings' based search for optimal sparse Bayesian networks via dynamic programming with parent set constraints. [PDF]
PLoS ONEIn our recent work, we developed a novel dynamic programming algorithm to find optimal Bayesian networks with parent set constraints. This 'generational orderings' based dynamic programming algorithm-CausNet-efficiently searches the space of possible ...
Nand Sharma, Joshua Millstein
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Cycles in Bayesian Networks [PDF]
International Journal of Electronics and Telecommunications, 2021 The article is devoted to some critical problems of using Bayesian networks for solving practical problems, in which graph models contain directed cycles.
Assem Shayakhmetova +4 more
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Practicalities of Bayesian network modeling for nuclear data evaluation with the nucdataBaynet package [PDF]
EPJ Web of Conferences, 2023 Bayesian networks are a helpful abstraction in the modelization of the relationships between different variables for the purpose of uncertainty quantification.
Schnabel Georg
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Semiparametric Bayesian networks
Information Sciences, 2022 We introduce semiparametric Bayesian networks that combine parametric and nonparametric conditional probability distributions. Their aim is to incorporate the advantages of both components: the bounded complexity of parametric models and the flexibility of nonparametric ones.
Atienza González, David +2 more
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Using consensus bayesian network to model the reactive oxygen species regulatory pathway. [PDF]
PLoS ONE, 2013 Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data ...
Liangdong Hu, Limin Wang
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Bayesian Network Classifiers [PDF]
Machine Learning, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Friedman, Nir +2 more
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Learning oncogenetic networks by reducing to mixed integer linear programming. [PDF]
PLoS ONE, 2013 Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events.
Hossein Shahrabi Farahani +1 more
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Spectral Bayesian network theory
Linear Algebra and its Applications, 2023 22 pages, 6 ...
Luke Duttweiler +2 more
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A Probability-based Evolutionary Algorithm with Mutations to Learn Bayesian Networks [PDF]
International Journal of Interactive Multimedia and Artificial Intelligence, 2014 Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that ...
Sho Fukuda +2 more
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Bayesian network–response regression [PDF]
Bioinformatics, 2017 Abstract Motivation There is increasing interest in learning how human brain networks vary as a function of a continuous trait, but flexible and efficient procedures to accomplish this goal are limited.
Wang, Lu +3 more
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