Résumé
Rich data are revealing that complex dependencies between the nodes of a network may not be captured by models based on pairwise interactions. Higher-order network models go beyond these limitations, offering new perspectives for understanding complex systems.
| langue originale | Anglais |
|---|---|
| Pages (de - à) | 313-320 |
| Nombre de pages | 8 |
| journal | Nature Physics |
| Volume | 15 |
| Numéro de publication | 4 |
| Les DOIs | |
| état | Publié - 1 avr. 2019 |
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From networks to optimal higher-order models of complex systems. / Lambiotte, Renaud; Rosvall, Martin; Scholtes, Ingo.
Dans: Nature Physics, Vol 15, Numéro 4, 01.04.2019, p. 313-320.Résultats de recherche: Contribution à un journal/une revue › Article de revue
TY - JOUR
T1 - From networks to optimal higher-order models of complex systems
AU - Lambiotte, Renaud
AU - Rosvall, Martin
AU - Scholtes, Ingo
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Rich data are revealing that complex dependencies between the nodes of a network may not be captured by models based on pairwise interactions. Higher-order network models go beyond these limitations, offering new perspectives for understanding complex systems.
AB - Rich data are revealing that complex dependencies between the nodes of a network may not be captured by models based on pairwise interactions. Higher-order network models go beyond these limitations, offering new perspectives for understanding complex systems.
UR - http://www.scopus.com/inward/record.url?scp=85063473600&partnerID=8YFLogxK
U2 - 10.1038/s41567-019-0459-y
DO - 10.1038/s41567-019-0459-y
M3 - Review article
VL - 15
SP - 313
EP - 320
JO - Nature Physics
JF - Nature Physics
SN - 1745-2473
IS - 4
ER -