Predicting discrete-time bifurcations with deep learning

Many natural and man-made systems are prone to critical transitions—abrupt and potentially devastating changes in dynamics. Deep learning classifiers can provide an early warning signal for critical transitions by learning generic features of bifurcations from large simulated training data sets. So...

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Detalles Bibliográficos
Autores principales: Bury, Thomas M., Dylewsky, Daniel, Bauch, Chris T., Anand, Madhur, Glass, Leon, Shrier, Alvin, Bub, Gil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564974/
https://www.ncbi.nlm.nih.gov/pubmed/37816722
http://dx.doi.org/10.1038/s41467-023-42020-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564974/
https://www.ncbi.nlm.nih.gov/pubmed/37816722
http://dx.doi.org/10.1038/s41467-023-42020-z

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