Artículo
Detecting the ultra low dimensionality of real networks
Autor/es | Almagro Blanco, Pedro
Boguñá, Marián Serrano, M. Ángeles |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2022 |
Fecha de depósito | 2022-11-23 |
Publicado en |
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Premios | Premio Mensual Publicación Científica Destacada de la US. Escuela Técnica Superior de Ingeniería Informática |
Resumen | Reducing dimension redundancy to find simplifying patterns in high dimensional datasets and complex networks has become a major endeavor
in many scientific fields. However, detecting the dimensionality of their latent
space ... Reducing dimension redundancy to find simplifying patterns in high dimensional datasets and complex networks has become a major endeavor in many scientific fields. However, detecting the dimensionality of their latent space is challenging but necessary to generate efficient embeddings to be used in a multitude of downstream tasks. Here, we propose a method to infer the dimensionality of networks without the need for any a priori spatial embed ding. Due to the ability of hyperbolic geometry to capture the complex con nectivity of real networks, we detect ultra low dimensionality far below values reported using other approaches. We applied our method to real networks from different domains and found unexpected regularities, including: tissue specific biomolecular networks being extremely low dimensional; brain con nectomes being close to the three dimensions of their anatomical embedding; and social networks and the Internet requiring slightly higher dimensionality. Beyond paving the way towards an ultra efficient dimensional reduction, our findings help address fundamental issues that hinge on dimensionality, such as universality in critical behavior. |
Agencias financiadoras | Agencia Estatal de Investigación. España Generalitat de Catalunya |
Identificador del proyecto | PID2019-106290GB-C22/AEI/10.13039/501100011033
2017SGR1064 |
Cita | Almagro Blanco, P., Boguñá, M. y Serrano, M.Á. (2022). Detecting the ultra low dimensionality of real networks. Nature Communications, 13 (art.nº6096), 1-10. https://doi.org/10.1038/s41467-022-33685-z. |
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