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  A hierarchical model for integrating unsupervised generative embedding and empirical Bayes

Raman, S., Deserno, L., Schlagenhauf, F., & Stephan, K. E. (2016). A hierarchical model for integrating unsupervised generative embedding and empirical Bayes. Journal of Neuroscience Methods, 269, 6-20. doi:10.1016/j.jneumeth.2016.04.022.

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 Creators:
Raman, Sudhir, Author
Deserno, Lorenz1, Author           
Schlagenhauf, Florian1, Author           
Stephan, Klaas Enno2, Author           
Affiliations:
1Max Planck Fellow Group Cognitive and Affective Control of Behavioural Adaptation, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1753350              
2Neuronal Control of Metabolism, Department Jens Brüning, Max Planck Institute for Metabolism Research, Managing Director: Jens Brüning, Max Planck Society, ou_2149644              

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Language(s): eng - English
 Dates: 2016
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.jneumeth.2016.04.022
 Degree: -

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Title: Journal of Neuroscience Methods
  Other : J. Neurosci. Meth.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 269 Sequence Number: - Start / End Page: 6 - 20 Identifier: ISSN: 0165-0270
CoNE: https://pure.mpg.de/cone/journals/resource/954925480594