Synthetic data generation with probabilistic Bayesian networks

DOI10.3934/mbe.2021426zbMath1501.92035OpenAlexW3207033141MaRDI QIDQ2092235

Grigoriy Gogoshin, Andrei Rodin, Sergio Branciamore

Publication date: 2 November 2022

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2021426

zbMATH Keywords

Bayesian networksdirected acyclic graphprobabilistic graphical modelsMarkov blanketcentral limitsynthetic data generation

Mathematics Subject Classification ID

Applications of graph theory (05C90) Computational methods for problems pertaining to biology (92-08) Systems biology, networks (92C42)

Uses Software

• TETRAD
• BANFF

Cites Work

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• Learning Bayesian networks: The combination of knowledge and statistical data
• On the asymptotic behavior of randomly weighted averages

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