107 citations · 218 across the 7 of their papers we have counts for
7 papers
Stochastic Chaos and Predictability in Laboratory Earthquakes
Adriano Gualandi, Davide Faranda, Chris Marone +2
Laboratory earthquakes exhibit characteristics of a low dimensional random attractor with a dimension similar to that of natural slow earthquakes. A model of stochastic differentia…
Deep learning for laboratory earthquake prediction and autoregressive forecasting of fault zone stress
Laura Laurenti, Elisa Tinti, Fabio Galasso +2
Earthquake forecasting and prediction have long and in some cases sordid histories but recent work has rekindled interest based on advances in early warning, hazard assessment for…
Attention network forecasts time-to-failure in laboratory shear experiments
Hope Jasperson, David C. Bolton, Paul Johnson +3
Rocks under stress deform by creep mechanisms that include formation and slip on small-scale internal cracks. Intragranular cracks and slip along grain contacts release energy as e…
Earthquake catalog-based machine learning identification of laboratory fault states and the effects of magnitude of completeness
Nicholas Lubbers, David C. Bolton, Jamaludin Mohd-Yusof +3
Machine learning regression can predict macroscopic fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions.…
Estimating the Physical State of a Laboratory Slow Slipping Fault from Seismic Signals
Claudia Hulbert, Bertrand Rouet-Leduc, Christopher X. Ren +4
Over the last two decades, strain and GPS measurements have shown that slow slip on earthquake faults is a widespread phenomenon. Slow slip is also inferred from correlated small a…
Estimating Fault Friction from Seismic Signals in the Laboratory
Bertrand Rouet-Leduc, Claudia Hulbert, David C. Bolton +5
Nearly all aspects of earthquake rupture are controlled by the friction along the fault that progressively increases with tectonic forcing, but in general cannot be directly measur…