Bayesian Workflow for Generative Modeling in Computational Psychiatry

Bayesian Workflow for Generative Modeling in Computational Psychiatry

Computational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been suggested which, however, has rarely been applied in Translat...

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Bibliographic Details
Main Authors: Alexander J. Hess, Sandra Iglesias, Laura Köchli, Stephanie Marino, Matthias Müller-Schrader, Lionel Rigoux, Christoph Mathys, Olivia K. Harrison, Jakob Heinzle, Stefan Frässle, Klaas Enno Stephan
Format: Article
Language:English
Published: Ubiquity Press 2025-03-01
Series:Computational Psychiatry
Subjects:
translational neuromodeling
computational psychiatry
bayesian workflow
hierarchical gaussian filter (hgf)
multimodal response models
robust inference
Online Access:https://account.cpsyjournal.org/index.php/up-j-cp/article/view/116
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https://account.cpsyjournal.org/index.php/up-j-cp/article/view/116

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