Cargando…
Beyond clustering: mean-field dynamics on networks with arbitrary subgraph composition
Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically manifests itself by a higher than expected frequency of triangles, and this has led to the principle of constructing networ...
Autores principales: | Ritchie, Martin, Berthouze, Luc, Kiss, Istvan Z. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4698307/ https://www.ncbi.nlm.nih.gov/pubmed/25893260 http://dx.doi.org/10.1007/s00285-015-0884-1 |
Ejemplares similares
-
Edge-Based Compartmental Modelling of an SIR Epidemic on a Dual-Layer Static–Dynamic Multiplex Network with Tunable Clustering
por: Barnard, Rosanna C., et al.
Publicado: (2018) -
Epidemic threshold in pairwise models for clustered networks: closures and fast correlations
por: Barnard, Rosanna C., et al.
Publicado: (2019) -
The Impact of Contact Structure and Mixing on Control Measures and Disease-Induced Herd Immunity in Epidemic Models: A Mean-Field Model Perspective
por: Di Lauro, Francesco, et al.
Publicado: (2021) -
Subgraphs of Interest Social Networks for Diffusion Dynamics Prediction
por: Guleva, Valentina Y., et al.
Publicado: (2021) -
Beyond dynamical mean-field theory of neural networks
por: Muratori, Massimiliano, et al.
Publicado: (2013)