Cargando…
Machine learning meets complex networks via coalescent embedding in the hyperbolic space
Physicists recently observed that realistic complex networks emerge as discrete samples from a continuous hyperbolic geometry enclosed in a circle: the radius represents the node centrality and the angular displacement between two nodes resembles their topological proximity. The hyperbolic circle ai...
| Autores principales: | , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2017
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5694768/ https://www.ncbi.nlm.nih.gov/pubmed/29151574 http://dx.doi.org/10.1038/s41467-017-01825-5 |