A hierarchical model for integrating unsupervised generative embedding and 
empirical Bayes

Raman, Sudhir; Deserno, Lorenz; Schlagenhauf, Florian; Stephan, Klaas Enno

doi:10.1016/j.jneumeth.2016.04.022

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A hierarchical model for integrating unsupervised generative embedding and empirical Bayes

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Deserno, Lorenz
Max Planck Fellow Group Cognitive and Affective Control of Behavioural Adaptation, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Schlagenhauf, Florian
Max Planck Fellow Group Cognitive and Affective Control of Behavioural Adaptation, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Stephan, Klaas Enno
Neuronal Control of Metabolism, Department Jens Brüning, Max Planck Institute for Metabolism Research, Managing Director: Jens Brüning, Max Planck Society;

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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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002A-D828-6

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