Learning self-driven collective dynamics with graph networks

Despite decades of theoretical research, the nature of the self-driven collective motion remains indigestible and controversial, while the phase transition process of its dynamic is a major research issue. Recent methods propose to infer the phase transition process from various artificially extract...

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Detalles Bibliográficos
Autores principales: Wang, Rui, Fang, Feiteng, Cui, Jiamei, Zheng, Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8752591/
https://www.ncbi.nlm.nih.gov/pubmed/35017588
http://dx.doi.org/10.1038/s41598-021-04456-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8752591/
https://www.ncbi.nlm.nih.gov/pubmed/35017588
http://dx.doi.org/10.1038/s41598-021-04456-5

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