Individualizing deep dynamic models for psychological resilience data

Deep learning approaches can uncover complex patterns in data. In particular, variational autoencoders achieve this by a non-linear mapping of data into a low-dimensional latent space. Motivated by an application to psychological resilience in the Mainz Resilience Project, which features intermitten...

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Detalles Bibliográficos
Autores principales: Köber, Göran, Pooseh, Shakoor, Engen, Haakon, Chmitorz, Andrea, Kampa, Miriam, Schick, Anita, Sebastian, Alexandra, Tüscher, Oliver, Wessa, Michèle, Yuen, Kenneth S. L., Walter, Henrik, Kalisch, Raffael, Timmer, Jens, Binder, Harald
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/PMC9110739/
https://www.ncbi.nlm.nih.gov/pubmed/35577829
http://dx.doi.org/10.1038/s41598-022-11650-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110739/
https://www.ncbi.nlm.nih.gov/pubmed/35577829
http://dx.doi.org/10.1038/s41598-022-11650-6

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