Flexible and efficient simulation-based inference for models of decision-making

Flexible and efficient simulation-based inference for models of decision-making

Inferring parameters of computational models that capture experimental data is a central task in cognitive neuroscience. Bayesian statistical inference methods usually require the ability to evaluate the likelihood of the model—however, for many models of interest in cognitive neuroscience, the asso...

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Bibliographic Details
Main Authors: Jan Boelts, Jan-Matthis Lueckmann, Richard Gao, Jakob H Macke
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2022-07-01
Series:eLife
Subjects:
computational modeling
decision-making
Bayesian inference
simulation-based inference
machine learning
Online Access:https://elifesciences.org/articles/77220

Internet

https://elifesciences.org/articles/77220

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