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Predicting fault slip via transfer learning

Data-driven machine-learning for predicting instantaneous and future fault-slip in laboratory experiments has recently progressed markedly, primarily due to large training data sets. In Earth however, earthquake interevent times range from 10’s-100’s of years and geophysical data typically exist for...

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Detalles Bibliográficos
Autores principales: Wang, Kun, Johnson, Christopher W., Bennett, Kane C., Johnson, Paul A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677738/
https://www.ncbi.nlm.nih.gov/pubmed/34916491
http://dx.doi.org/10.1038/s41467-021-27553-5