Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints

Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. Rooted into statistical physics, the ERGMs framework has been successfully employed for reconstructing networks, detecting statistically significant patterns in graphs, counting networked configurations with gi...

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Detalles Bibliográficos
Autores principales: Vallarano, Nicolò, Bruno, Matteo, Marchese, Emiliano, Trapani, Giuseppe, Saracco, Fabio, Cimini, Giulio, Zanon, Mario, Squartini, Tiziano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316481/
https://www.ncbi.nlm.nih.gov/pubmed/34315920
http://dx.doi.org/10.1038/s41598-021-93830-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316481/
https://www.ncbi.nlm.nih.gov/pubmed/34315920
http://dx.doi.org/10.1038/s41598-021-93830-4

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