Hypergraph reconstruction from network data
نویسندگان
چکیده
Abstract Networks can describe the structure of a wide variety complex systems by specifying which pairs entities in system are connected. While such pairwise representations flexible, they not necessarily appropriate when fundamental interactions involve more than two at same time. Pairwise nonetheless remain ubiquitous, because higher-order often recorded explicitly network data. Here, we introduce Bayesian approach to reconstruct latent from ordinary Our method is based on principle parsimony and only includes structures there sufficient statistical evidence for them. We demonstrate its applicability range datasets, both synthetic empirical.
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ژورنال
عنوان ژورنال: Communications physics
سال: 2021
ISSN: ['2399-3650']
DOI: https://doi.org/10.1038/s42005-021-00637-w