Variability in higher order structure of noise added to weighted networks

A common problem in reconstructing weighted networks to represent real-world systems is that low-weight edges might appear due to noise, affecting the topology of the inferred network. Here, the authors propose a method based on persistent homology that allows one to investigate the higher-order net...

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Autores principales:	Ann S. Blevins, Jason Z. Kim, Dani S. Bassett
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Astrophysics QB460-466 Physics QC1-999
Acceso en línea:	https://doaj.org/article/aee7cd2648e549649747b3a17be0d7aa
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spelling	oai:doaj.org-article:aee7cd2648e549649747b3a17be0d7aa2021-11-08T10:58:03ZVariability in higher order structure of noise added to weighted networks10.1038/s42005-021-00725-x2399-3650https://doaj.org/article/aee7cd2648e549649747b3a17be0d7aa2021-11-01T00:00:00Zhttps://doi.org/10.1038/s42005-021-00725-xhttps://doaj.org/toc/2399-3650A common problem in reconstructing weighted networks to represent real-world systems is that low-weight edges might appear due to noise, affecting the topology of the inferred network. Here, the authors propose a method based on persistent homology that allows one to investigate the higher-order network organization that can be created by low-weight, noisy edges.Ann S. BlevinsJason Z. KimDani S. BassettNature PortfolioarticleAstrophysicsQB460-466PhysicsQC1-999ENCommunications Physics, Vol 4, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Astrophysics QB460-466 Physics QC1-999
spellingShingle	Astrophysics QB460-466 Physics QC1-999 Ann S. Blevins Jason Z. Kim Dani S. Bassett Variability in higher order structure of noise added to weighted networks
description	A common problem in reconstructing weighted networks to represent real-world systems is that low-weight edges might appear due to noise, affecting the topology of the inferred network. Here, the authors propose a method based on persistent homology that allows one to investigate the higher-order network organization that can be created by low-weight, noisy edges.
format	article
author	Ann S. Blevins Jason Z. Kim Dani S. Bassett
author_facet	Ann S. Blevins Jason Z. Kim Dani S. Bassett
author_sort	Ann S. Blevins
title	Variability in higher order structure of noise added to weighted networks
title_short	Variability in higher order structure of noise added to weighted networks
title_full	Variability in higher order structure of noise added to weighted networks
title_fullStr	Variability in higher order structure of noise added to weighted networks
title_full_unstemmed	Variability in higher order structure of noise added to weighted networks
title_sort	variability in higher order structure of noise added to weighted networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/aee7cd2648e549649747b3a17be0d7aa
work_keys_str_mv	AT annsblevins variabilityinhigherorderstructureofnoiseaddedtoweightednetworks AT jasonzkim variabilityinhigherorderstructureofnoiseaddedtoweightednetworks AT danisbassett variabilityinhigherorderstructureofnoiseaddedtoweightednetworks
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Variability in higher order structure of noise added to weighted networks

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