Deep learning of aftershock patterns following large earthquakes

• Published in: Nature (London) Vol. 560; no. 7720; pp. 632 - 634
• Main Authors: DeVries, Phoebe M. R., Viégas, Fernanda, Wattenberg, Martin, Meade, Brendan J.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.08.2018; Nature Publishing Group
• Subjects: 704/2151/508; 704/2151/562; 704/4111; Aftershocks; Artificial neural networks; Datasets; Deep learning; Earthquake prediction; Earthquakes; Humanities and Social Sciences; Laws, regulations and rules; Letter; Machine learning; multidisciplinary; Neural networks; Observatories; Plate tectonics; Science; Science (multidisciplinary); Seismic activity; Seismic response; Seismology; Shear stress; Spatial distribution; Yield criteria; Peru; Indonesia; Costa Rica

Aftershocks are a response to changes in stress generated by large earthquakes and represent the most common observations of the triggering of earthquakes. The maximum magnitude of aftershocks and their temporal decay are well described by empirical laws (such as Bath’s law 1 and Omori’s law 2 ), bu...