Intermittent criticality multi‐scale processes leading to large slip events on rough laboratory faults
We discuss data of three laboratory stick‐slip experiments on Westerly Granite samples
performed at elevated confining pressure and constant displacement rate on rough fracture …
performed at elevated confining pressure and constant displacement rate on rough fracture …
Empowering machine learning forecasting of labquake using event‐based features and clustering characteristics
S Karimpouli, G Kwiatek, Y Ben‐Zion… - Journal of …, 2024 - Wiley Online Library
Following recent advances of machine learning (ML), we present a novel approach to
extract spatiotemporal seismo‐mechanical features from Acoustic Emission (AE) catalogs to …
extract spatiotemporal seismo‐mechanical features from Acoustic Emission (AE) catalogs to …
Probing the Evolution of Fault Properties During the Seismic Cycle with Deep Learning
We use seismic waves that pass through the hypocentral region of the 2016 M6. 5 Norcia
earthquake together with Deep Learning (DL) to distinguish between foreshocks …
earthquake together with Deep Learning (DL) to distinguish between foreshocks …