Non-homogeneous dynamic Bayesian networks with edge-wise sequentially coupled parameters

MOTIVATION: Non-homogeneous dynamic Bayesian networks (NH-DBNs) are a popular tool for learning networks with time-varying interaction parameters. A multiple changepoint process is used to divide the data into disjoint segments and the network interaction parameters are assumed to be segment-specifi...

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Detalles Bibliográficos
Autores principales: Shafiee Kamalabad, Mahdi, Grzegorczyk, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703764/
https://www.ncbi.nlm.nih.gov/pubmed/31504191
http://dx.doi.org/10.1093/bioinformatics/btz690

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703764/
https://www.ncbi.nlm.nih.gov/pubmed/31504191
http://dx.doi.org/10.1093/bioinformatics/btz690

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