Machine learning and earthquake forecasting—next steps

Gregory C. Beroza (), Margarita Segou and S. Mostafa Mousavi
Additional contact information
Gregory C. Beroza: Stanford University
Margarita Segou: Lyell Centre
S. Mostafa Mousavi: Stanford University

Nature Communications, 2021, vol. 12, issue 1, 1-3

Abstract: A new generation of earthquake catalogs developed through supervised machine-learning illuminates earthquake activity with unprecedented detail. Application of unsupervised machine learning to analyze the more complete expression of seismicity in these catalogs may be the fastest route to improving earthquake forecasting.

Date: 2021
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DOI: 10.1038/s41467-021-24952-6

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