From Labquakes to Megathrusts: Scaling Deep Learning Based Pickers Over 15 Orders of Magnitude

From Labquakes to Megathrusts: Scaling Deep Learning Based Pickers Over 15 Orders of Magnitude

Abstract The application of machine learning techniques in seismology has greatly advanced seismological analysis, especially for earthquake detection and seismic phase picking. However, machine learning approaches still face challenges in generalizing to data sets that differ from their original tr...

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Main Authors: Peidong Shi, Men‐Andrin Meier, Linus Villiger, Katinka Tuinstra, Paul Antony Selvadurai, Federica Lanza, Sanyi Yuan, Anne Obermann, Maria Mesimeri, Jannes Münchmeyer, Patrick Bianchi, Stefan Wiemer
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:Journal of Geophysical Research: Machine Learning and Computation
Subjects:
machine learning
earthquake monitoring
labquake
rescaling
seismic phase picking
out of distribution generalization
Online Access:https://doi.org/10.1029/2024JH000220
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https://doi.org/10.1029/2024JH000220

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