“Stealing fire or stacking knowledge” by machine intelligence to model link prediction in complex networks

Current methodologies to model connectivity in complex networks either rely on network scientists’ intelligence to discover reliable physical rules or use artificial intelligence (AI) that stacks hundreds of inaccurate human-made rules to make a new one that optimally summarizes them together. Here,...

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Detalles Bibliográficos
Autores principales: Muscoloni, Alessandro, Cannistraci, Carlo Vittorio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9771718/
https://www.ncbi.nlm.nih.gov/pubmed/36570772
http://dx.doi.org/10.1016/j.isci.2022.105697

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9771718/
https://www.ncbi.nlm.nih.gov/pubmed/36570772
http://dx.doi.org/10.1016/j.isci.2022.105697

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