Inference of time-ordered multibody interactions
Physics and Society
2023-10-17 v2 Data Analysis, Statistics and Probability
Machine Learning
Abstract
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.
Cite
@article{arxiv.2111.14611,
title = {Inference of time-ordered multibody interactions},
author = {Unai Alvarez-Rodriguez and Luka V. Petrović and Ingo Scholtes},
journal= {arXiv preprint arXiv:2111.14611},
year = {2023}
}
Comments
16 pages, 10 figures