Bayesian mixed-effects inference on classification performance in hierarchical data sets. - Kay Henning Brodersen; Christoph Mathys; Justin R. Chumbley; Jean Daunizeau; Cheng Soon Ong; Joachim M. Buhmann; Klaas E. Stephan (J. Mach. Learn. Res., 2012)

Variational Bayesian mixed-effects inference for classification studies. - Kay Henning Brodersen; Jean Daunizeau; Christoph Mathys; Justin R. Chumbley; Joachim M. Buhmann; Klaas E. Stephan (NeuroImage, 2013)

Inferring on the Intentions of Others by Hierarchical Bayesian Learning. - Andreea Oliviana Diaconescu; Christoph Mathys; Lilian A. E. Weber; Jean Daunizeau; Lars Kasper; Ekaterina I. Lomakina; Ernst Fehr; Klaas E. Stephan (PLoS Comput. Biol., 2014)

Scene Construction, Visual Foraging, and Active Inference. - M. Berk Mirza; Rick A. Adams; Christoph Mathys; Karl J. Friston (Frontiers Comput. Neurosci., 2016)

A unifying Bayesian account of contextual effects in value-based choice. - Francesco Rigoli; Christoph Mathys; Karl J. Friston; Raymond J. Dolan (PLoS Comput. Biol., 2017)

Modeling subjective relevance in schizophrenia and its relation to aberrant salience. - Teresa Katthagen; Christoph Mathys; Lorenz Deserno; Henrik Walter; Norbert Kathmann; Andreas Heinz; Florian Schlagenhauf (PLoS Comput. Biol., 2018)

Dynamic causal modelling revisited. - Karl J. Friston; Katrin H. Preller; Christoph Mathys; Hayriye Cagnan; Jakob Heinzle; Adeel Razi; Peter Zeidman (NeuroImage, 2019)

Correction: A unifying Bayesian account of contextual effects in value-based choice. - Francesco Rigoli; Christoph Mathys; Karl J. Friston; Raymond J. Dolan (PLoS Comput. Biol., 2019)

Hierarchical Gaussian Filtering of Sufficient Statistic Time Series for Active Inference. - Christoph Mathys; Lilian A. E. Weber (IWAI, 2020)

Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder. - Lara Henco; Andreea O. Diaconescu; Juha M. Lahnakoski; Marie-Luise Brandi; Sophia Hörmann; Johannes Hennings; Alkomiet Hasan; Irina Papazova; Wolfgang Strube; Dimitris Bolis; Leonhard Schilbach; Christoph Mathys (PLoS Comput. Biol., 2020)

The Switching Hierarchical Gaussian Filter. - Ismail Senöz; Albert Podusenko; Semih Akbayrak; Christoph Mathys; Bert de Vries (ISIT, 2021)

Rule Learning Through Active Inductive Inference. - Tore Erdmann; Christoph Mathys (PKDD/ECML Workshops (1), 2021)

Inferring in Circles: Active Inference in Continuous State Space Using Hierarchical Gaussian Filtering of Sufficient Statistics. - Peter Thestrup Waade; Nace Mikus; Christoph Mathys (PKDD/ECML Workshops (1), 2021)

Cholinergic and dopaminergic effects on prediction error and uncertainty responses during sensory associative learning. - Sandra Iglesias; Lars Kasper; Samuel J. Harrison; Robert Manka; Christoph Mathys; Klaas E. Stephan (NeuroImage, 2021)

The generalized Hierarchical Gaussian Filter. - Lilian Aline Weber; Peter Thestrup Waade; Nicolas Legrand; Anna Hedvig Møller; Klaas Enno Stephan; Christoph Mathys (CoRR, 2023)

Phi fluctuates with surprisal: An empirical pre-study for the synthesis of the free energy principle and integrated information theory. - Christoffer Lundbak Olesen; Peter Thestrup Waade; Larissa Albantakis; Christoph Mathys (PLoS Comput. Biol., 2023)

Hippocampal Processing of Levels of Uncertainty and Environmental Volatility. OPM-MEG Correlates of Learning Through Levels of Uncertainty by a Hierarchical Gaussian Filter. - Marta Suárez-Pinilla; Holly Schofield; Ryan M. Hill; Matthew J. Brookes; Christoph Mathys; Bryan Strange (MetroXRAINE, 2024)

pyhgf: A neural network library for predictive coding. - Nicolas Legrand; Lilian Aline Weber; Peter Thestrup Waade; Anna Hedvig Møller Daugaard; Mojtaba Khodadadi; Nace Mikus; Christoph Mathys (CoRR, 2024)