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Understanding complex systems: from networks to optimal higher-order models

Abstract:

To better understand the structure and function of complex systems, researchers often represent direct interactions between components in complex systems with networks, assuming that indirect influence between distant components can be modelled by paths. Such network models assume that actual paths are memoryless. That is, the way a path continues as it passes through a node does not depend on where it came from. Recent studies of data on actual paths in complex systems question this assumpti...

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Publication status:
Not published
Peer review status:
Not peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Oxford college:
Somerville College
Role:
Author
ORCID:
0000-0002-0583-4595
Publication date:
2018-06-14
Source identifiers:
859667
Keywords:
Pubs id:
pubs:859667
UUID:
uuid:dccc2a59-71b5-4815-9ee6-ba6e572bb846
Local pid:
pubs:859667
Deposit date:
2018-07-27

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