126 citations · 127 across the 3 of their papers we have counts for
4 papers
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…
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…
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…