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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...
Autores principales: | Vallarano, Nicolò, Bruno, Matteo, Marchese, Emiliano, Trapani, Giuseppe, Saracco, Fabio, Cimini, Giulio, Zanon, Mario, Squartini, Tiziano |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
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 |
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