Christoph Mathys

According to our database, Christoph Mathys authored at least 20 papers between 2012 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference.

Peter Thestrup Waade, Christoffer Lundbak Olesen, Jonathan Ehrenreich Laursen, Samuel William Nehrer, Conor Heins, Karl John Friston, Christoph Mathys

Entropy, 2025

2024

Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models.

Samuel William Nehrer, Jonathan Ehrenreich Laursen, Conor Heins, Karl J. Friston, Christoph Mathys, Peter Thestrup Waade

Entropy, 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

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

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2024

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., October, 2023

The generalized Hierarchical Gaussian Filter.

Lilian Aline Weber, Peter Thestrup Waade, Nicolas Legrand, Anna Hedvig Møller, Klaas Enno Stephan, Christoph Mathys

CoRR, 2023

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

Inferring in Circles: Active Inference in Continuous State Space Using Hierarchical Gaussian Filtering of Sufficient Statistics.

Peter Thestrup Waade, Nace Mikus, Christoph Mathys

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Rule Learning Through Active Inductive Inference.

Tore Erdmann, Christoph Mathys

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

The Switching Hierarchical Gaussian Filter.

Ismail Senöz, Albert Podusenko, Semih Akbayrak, Christoph Mathys, Bert de Vries

Proceedings of the IEEE International Symposium on Information Theory, 2021

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

Hierarchical Gaussian Filtering of Sufficient Statistic Time Series for Active Inference.

Christoph Mathys, Lilian A. E. Weber

Proceedings of the Active Inference - First International Workshop, 2020

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

Dynamic causal modelling revisited.

Karl J. Friston, Katrin H. Preller, Christoph Mathys, Hayriye Cagnan, Jakob Heinzle, Adeel Razi, Peter Zeidman

NeuroImage, 2019

2018

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

2017

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

2016

Scene Construction, Visual Foraging, and Active Inference.

M. Berk Mirza, Rick A. Adams, Christoph Mathys, Karl J. Friston

Frontiers Comput. Neurosci., 2016

2014

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

2013

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

2012

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