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Fast Möbius transform: An algebraic approach to information decomposition

Abel Jansma ^1,2,3,*, Pedro A. M. Mediano ^4,5,†, and Fernando E. Rosas^6,7,8,9,‡

¹Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
²School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
³Dutch Institute for Emergent Phenomena, University of Amsterdam, Amsterdam, the Netherlands
⁴Department of Computing, Imperial College London, London, United Kingdom
⁵Division of Psychology and Language Sciences, University College London, London, United Kingdom
⁶Sussex AI and Sussex Centre for Consciousness Science, Department of Informatics, University of Sussex, Brighton, United Kingdom
⁷Principles of Intelligent Behavior in Biological and Social Systems (PIBBSS), Prague, Czech Republic
⁸Center for Psychedelic Research and Centre for Complexity Science, Department of Brain Science, Imperial College London, London, United Kingdom
⁹Center for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom

^*Contact author: a.a.a.jansma@uva.nl
^†Contact author: p.mediano@imperial.ac.uk
^‡Contact author: f.rosas@sussex.ac.uk

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Articles Citing

Fast Möbius transform: An algebraic approach to information decomposition

Emergent multiscale organisation of neural dynamics fragments in anaesthesia

DFGNet: A dual-pathway graph neural network via frequency decomposition for spatiotemporal forecasting

A scalable estimator of higher-order information in complex dynamical systems

No title available

Increased integration and synergy in EEG- and fNIRS-based data in migraine patients after a three-month treatment with galcanezumab: relations with long-term clinical outcome

Characterising high-order interdependence via entropic conjugation

Associative conditioning in gene regulatory network models increases integrative causal emergence

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