Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data

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Latent Variable Models (LVMs) are well established tools to accomplish a range of different data processing tasks. Applications exploit the ability of LVMs to identify latent data structure in order to improve data (e.g., through denoising) or to estimate the relation between latent causes and measu...

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Detalles Bibliográficos
Autores principales: Mousavi, Hamid, Buhl, Mareike, Guiraud, Enrico, Drefs, Jakob, Lücke, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145930/
https://www.ncbi.nlm.nih.gov/pubmed/33947060
http://dx.doi.org/10.3390/e23050552

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145930/
https://www.ncbi.nlm.nih.gov/pubmed/33947060
http://dx.doi.org/10.3390/e23050552

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