126 citations · 129 across the 5 of their papers we have counts for
6 papers
Deep learning detects uncataloged low-frequency earthquakes across regions
Jannes Münchmeyer, Sophie Giffard-Roisin, Marielle Malfante +4
Documenting the interplay between slow deformation and seismic ruptures is essential to understand the physics of earthquakes nucleation. However, slow deformation is often difficu…
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…
HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognition
Leon Weber, Mario Sänger, Jannes Münchmeyer +3
Summary: Named Entity Recognition (NER) is an important step in biomedical information extraction pipelines. Tools for NER should be easy to use, cover multiple entity types, highl…
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
Leon Weber, Pasquale Minervini, Jannes Münchmeyer +2
Rule-based models are attractive for various tasks because they inherently lead to interpretable and explainable decisions and can easily incorporate prior knowledge. However, such…