A Bayesian generative neural network framework for epidemic inference problems

The reconstruction of missing information in epidemic spreading on contact networks can be essential in the prevention and containment strategies. The identification and warning of infectious but asymptomatic individuals (i.e., contact tracing), the well-known patient-zero problem, or the inference...

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Detalles Bibliográficos
Autores principales: Biazzo, Indaco, Braunstein, Alfredo, Dall’Asta, Luca, Mazza, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667449/
https://www.ncbi.nlm.nih.gov/pubmed/36385141
http://dx.doi.org/10.1038/s41598-022-20898-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667449/
https://www.ncbi.nlm.nih.gov/pubmed/36385141
http://dx.doi.org/10.1038/s41598-022-20898-x

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