153 citations · 588 across the 9 of their papers we have counts for
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physics.geo-ph2022★ 72 cited
Earthquake Phase Association with Graph Neural Networks
Ian W. McBrearty, Gregory C. Beroza
Seismic phase association connects earthquake arrival time measurements to their causative sources. Effective association must determine the number of discrete events, their locati…
physics.geo-ph2022★ 96 cited
QuakeFlow: A Scalable Machine-learning-based Earthquake Monitoring Workflow with Cloud Computing
Weiqiang Zhu, Alvin Brian Hou, Robert Yang +4
Earthquake monitoring workflows are designed to detect earthquake signals and to determine source characteristics from continuous waveform data. Recent developments in deep learnin…
physics.geo-ph2022★ 29 cited
Earthquake Location and Magnitude Estimation with Graph Neural Networks
Ian W. McBrearty, Gregory C. Beroza
We solve the traditional problems of earthquake location and magnitude estimation through a supervised learning approach, where we train a Graph Neural Network to predict estimates…