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Belief propagation on networks with cliques and chordless cycles
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dc.contributor.author | Mann, Peter Stephen | |
dc.contributor.author | Dobson, Simon Andrew | |
dc.date.accessioned | 2023-05-09T11:30:06Z | |
dc.date.available | 2023-05-09T11:30:06Z | |
dc.date.issued | 2023-05-08 | |
dc.identifier.citation | Mann , P S & Dobson , S A 2023 , ' Belief propagation on networks with cliques and chordless cycles ' , Physical Review E , vol. 107 , 054303 . https://doi.org/10.1103/PhysRevE.107.054303 | en |
dc.identifier.issn | 1539-3755 | |
dc.identifier.other | PURE: 284094874 | |
dc.identifier.other | PURE UUID: 5ebcb35b-4e1e-4078-8a30-0599277b833e | |
dc.identifier.other | ORCID: /0000-0001-9633-2103/work/135019289 | |
dc.identifier.other | Scopus: 85159668374 | |
dc.identifier.uri | https://hdl.handle.net/10023/27538 | |
dc.description | Funding: This work was partially supported by the UK Engineering and Physical Sciences Research Council under grant number EP/N007565/1 (Science of Sensor Systems Software). | en |
dc.description.abstract | It is well known that tree-based theories can describe the properties of undirected clustered networks with extremely accurate results [S. Melnik, et al. Phys. Rev. E 83, 036112 (2011)]. It is reasonable to suggest that a motif based theory would be superior to a tree one; since additional neighbour correlations are encapsulated in the motif structure. In this paper we examine bond percolation on random and real world networks using belief propagation in conjunction with edge-disjoint motif covers. We derive exact message passing expressions for cliques and chordless cycles of finite size. Our theoretical model gives good agreement with Monte Carlo simulation and offers a simple, yet substantial improvement on traditional message passing showing that this approach is suitable to study the properties of random and empirical networks. | |
dc.format.extent | 13 | |
dc.language.iso | eng | |
dc.relation.ispartof | Physical Review E | en |
dc.rights | Copyright © 2023 American Physical Society. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the final published version of the work, which was originally published at https://doi.org/10.1103/PhysRevE.107.054303. | en |
dc.subject | Complex networks | en |
dc.subject | Belief propagation | en |
dc.subject | Clustering | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | QC Physics | en |
dc.subject | T-NDAS | en |
dc.subject | MCC | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | QC | en |
dc.title | Belief propagation on networks with cliques and chordless cycles | en |
dc.type | Journal article | en |
dc.contributor.sponsor | EPSRC | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.contributor.institution | University of St Andrews. Sir James Mackenzie Institute for Early Diagnosis | en |
dc.identifier.doi | https://doi.org/10.1103/PhysRevE.107.054303 | |
dc.description.status | Peer reviewed | en |
dc.date.embargoedUntil | 2023-05-08 | |
dc.identifier.grantnumber | EP/N007565/1 | en |
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