T Gneiting, M Katzfuss - Annual Review of Statistics and Its …, 2014 - annualreviews.org
A probabilistic forecast takes the form of a predictive probability distribution over future quantities or events of interest. Probabilistic forecasting aims to maximize the sharpness of …
Immediately after a large earthquake, the main question asked by the public and decision- makers is whether it was the mainshock or a foreshock to an even stronger event yet to …
We apply machine learning to data sets from shear laboratory experiments, with the goal of identifying hidden signals that precede earthquakes. Here we show that by listening to the …
EH Field, RJ Arrowsmith, GP Biasi… - Bulletin of the …, 2014 - pubs.geoscienceworld.org
Abstract The 2014 Working Group on California Earthquake Probabilities (WGCEP14) present the time‐independent component of the Uniform California Earthquake Rupture …
This essential reference for graduate students and researchers provides a unified treatment of earthquakes and faulting as two aspects of brittle tectonics at different timescales. The …
Seismic hazard modeling is a multidisciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such models consist of a probabilistic …
The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our …
EH Field, GP Biasi, P Bird… - Bulletin of the …, 2015 - pubs.geoscienceworld.org
Abstract The 2014 Working Group on California Earthquake Probabilities (WGCEP 2014) presents time‐dependent earthquake probabilities for the third Uniform California …