213 citations · 466 across the 7 of their papers we have counts for
8 papers
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…
PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning
Thomas Bornstein, Dietrich Lange, Jannes Münchmeyer +5
Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data machine lear…
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…
A probabilistic view on rupture predictability: all earthquakes evolve similarly
Jannes Münchmeyer, Ulf Leser, Frederik Tilmann
Ruptures of the largest earthquakes can last between a few seconds and several minutes. An early assessment of the final earthquake size is essential for early warning systems. How…
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…
Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers
Jannes Münchmeyer, Jack Woollam, Andreas Rietbrock +10
Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significant…
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…
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…