213 citations · 530 across the 13 of their papers we have counts for
14 papers
Towards End-to-End Earthquake Monitoring Using a Multitask Deep Learning Model
Weiqiang Zhu, Junhao Song, Haoyu Wang +1
Seismic waveforms contain rich information about earthquake processes, making effective data analysis crucial for earthquake monitoring, source characterization, and seismic hazard…
A Global-scale Database of Seismic Phases from Cloud-based Picking at Petabyte Scale
Yiyu Ni, Marine A. Denolle, Amanda M. Thomas +6
We present the first global-scale database of 4.3 billion P- and S-wave picks extracted from 1.3 PB continuous seismic data via a cloud-native workflow. Using cloud computing servi…
Seismic swarms unveil the mechanisms driving shallow slow slip dynamics in the Copiapó ridge, Northern Chile
Jannes Münchmeyer, Diego Molina, Mathilde Radiguet +6
Like earthquakes, slow slip events release elastic energy stored on faults. Yet, the mechanisms behind slow slip instability and its relationship with seismicity are debated. Here,…
SeisLM: a Foundation Model for Seismic Waveforms
Tianlin Liu, Jannes Münchmeyer, Laura Laurenti +3
We introduce the Seismic Language Model (SeisLM), a foundational model designed to analyze seismic waveforms -- signals generated by Earth's vibrations such as the ones originating…
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…
PyOcto: A high-throughput seismic phase associator
Jannes Münchmeyer
Seismic phase association is an essential task for characterising seismicity: given a collection of phase picks, identify all seismic events in the data. In recent years, machine l…
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…
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…
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…