3 papers
physics.geo-ph2026
Probabilistic and Alarm-Based Evaluation of a b-Value-Driven Deep Learning Earthquake Forecast
Jonas Köhler, Wei Li, Johannes Faber +2
We evaluate the forecasting performance of a deep learning model, originally introduced as a pattern-extraction framework, that operates on the spatiotemporal evolution of seismic…
physics.geo-ph2026
Detecting Spatiotemporal b-Value Anomalies with a Progressive Deep Learning Architecture
Jonas Köhler, Wei Li, Johannes Faber +2
Identifying systematic patterns in seismicity that precede large earthquakes remains a central challenge in statistical seismology. In this work, we present a methodological framew…
physics.geo-ph2025
A Deep Learning Pipeline for Large Earthquake Analysis using High-Rate Global Navigation Satellite System Data
Claudia Quinteros-Cartaya, Javier Quintero-Arenas, Andrea Padilla-Lafarga +5
Deep learning techniques for processing large and complex datasets have unlocked new opportunities for fast and reliable earthquake analysis using Global Navigation Satellite Syste…