Results 11 to 20 of about 80,384 (252)

CausNet-partial: 'Partial Generational Orderings' based search for optimal sparse Bayesian networks via dynamic programming with parent set constraints. [PDF]

PLoS ONE
In 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
doaj   +2 more sources

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, Natalya Litvinenko, Orken Mamyrbayev, Waldemar Wójcik, Dusmat Zhamangarin   +4 more
doaj   +1 more source

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
doaj   +1 more source

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, Bielza Lozoya, María Concepción, Larrañaga Múgica, Pedro María   +2 more
openaire   +3 more sources

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
doaj   +1 more source

Bayesian Network Classifiers [PDF]

Machine Learning, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Friedman, Nir, Geiger, Dan, Goldszmidt, Moises   +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, Jens Lagergren   +1 more
doaj   +1 more source

Spectral Bayesian network theory

Linear Algebra and its Applications, 2023
22 pages, 6 ...
Luke Duttweiler, Sally W. Thurston, Anthony Almudevar   +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, DURANTE, DANIELE, Jung, Rex E., Dunson, David B.   +3 more
openaire   +4 more sources

From heterogeneous healthcare data to disease-specific biomarker networks: A hierarchical Bayesian network approach.

PLoS Computational Biology, 2021
In this work, we introduce an entirely data-driven and automated approach to reveal disease-associated biomarker and risk factor networks from heterogeneous and high-dimensional healthcare data.
Ann-Kristin Becker, Marcus Dörr, Stephan B Felix, Fabian Frost, Hans J Grabe, Markus M Lerch, Matthias Nauck, Uwe Völker, Henry Völzke, Lars Kaderali   +9 more
doaj   +1 more source