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20202025
most citedEarthquake magnitude and location estimation from real time seismic waveforms with a transformer network

126 citations · 127 across the 4 of their papers we have counts for

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5 papers · 1 filter

physics.geo-ph2025

Characterising the Atacama segment of the Chile subduction margin (24°S-31°S) with >165,000 earthquakes

Jannes Münchmeyer, Diego Molina-Ormazabal, David Marsan +8

The Atacama segment in Northern Chile (24°S to 31°S) is a mature seismic gap with no major event (Mw>8) since 1922. In addition to regular seismicity, around the subducting Copiapó…

physics.geo-ph2022

Machine learning event detection workflows in practice: A case study from the 2019 Durrës aftershock sequence

Jack Woollam, Vincent Van der Heiden, Andreas Rietbrock +3

Machine Learning (ML) methods have demonstrated exceptional performance in recent years when applied to the task of seismic event detection. With numerous ML techniques now availab…

physics.geo-ph20211 cited

SeisBench -- A Toolbox for Machine Learning in Seismology

Jack Woollam, Jannes Münchmeyer, Frederik Tilmann +10

Machine Learning (ML) methods have seen widespread adoption in seismology in recent years. The ability of these techniques to efficiently infer the statistical properties of large…

physics.geo-ph2021126 cited

Earthquake magnitude and location estimation from real time seismic waveforms with a transformer network

Jannes Münchmeyer, Dino Bindi, Ulf Leser +1

Precise real time estimates of earthquake magnitude and location are essential for early warning and rapid response. While recently multiple deep learning approaches for fast asses…

physics.geo-ph2020

The transformer earthquake alerting model: A new versatile approach to earthquake early warning

Jannes Münchmeyer, Dino Bindi, Ulf Leser +1

Earthquakes are major hazards to humans, buildings and infrastructure. Early warning methods aim to provide advance notice of incoming strong shaking to enable preventive action an…