Inference of time-ordered multibody interactions
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Abstract (arXiv)
We introduce time-ordered multibody interactions to describe complex systems manifesting temporal as well as multibody dependencies. First, we show how the dynamics of multivariate Markov chains can be decomposed in ensembles of time-ordered multibody interactions. Then, we present an algorithm to extract those interactions from data capturing the system-level dynamics of node states and a measure to characterize the complexity of interaction ensembles. Finally, we experimentally validate the robustness of our algorithm against statistical errors and its efficiency at inferring parsimonious interaction ensembles.
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References · 7
- 2020Networks beyond pairwise interactions: structure and dynamicscited by 127
- 2016Higher-order organization of complex networkscited by 109
- 2013Multilayer Networkscited by 86
- 2021The physics of higher-order interactions in complex systemscited by 63
- 2014The structure and dynamics of multilayer networkscited by 51
- 2015Modern temporal network theory: A colloquiumcited by 23
- 2020Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate datacited by 16
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