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Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature

Describing networks geometrically through low-dimensional latent metric spaces has helped design efficient learning algorithms, unveil network symmetries and study dynamical network processes. However, latent space embeddings are limited to specific classes of networks because incompatible metric sp...

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Detalles Bibliográficos
Autores principales: Gosztolai, Adam, Arnaudon, Alexis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316456/
https://www.ncbi.nlm.nih.gov/pubmed/34315911
http://dx.doi.org/10.1038/s41467-021-24884-1