4 citations · 5 across the 5 of their papers we have counts for
8 papers · 1 filter
Autonomous Detection of Methane Emissions in Multispectral Satellite Data Using Deep Learning
Bertrand Rouet-Leduc, Thomas Kerdreux, Alexandre Tuel +1
Methane is one of the most potent greenhouse gases, and its short atmospheric half-life makes it a prime target to rapidly curb global warming. However, current methane emission mo…
Tremor Waveform Denoising and Automatic Location with Neural Network Interpretation
Claudia Hulbert, Romain Jolivet, Blandine Gardonio +3
Active faults release tectonic stress imposed by plate motion through a spectrum of slip modes, from slow, aseismic slip, to dynamic, seismic events. Slow earthquakes are often ass…
Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano
C. X. Ren, A. Peltier, V. Ferrazzini +3
Volcanic tremor is key to our understanding of active magmatic systems but, due to its complexity, there is still a debate concerning its origins and how it can be used to characte…
A Silent Build-up in Seismic Energy Precedes Slow Slip Failure in the Cascadia Subduction Zone
Claudia Hulbert, Bertrand Rouet-Leduc, Paul A. Johnson
We report on slow earthquakes in Northern Cascadia, and show that continuous seismic energy in the subduction zone follows specific patterns leading to failure. We rely on machine…
Probing slow earthquakes with deep learning
Bertrand Rouet-Leduc, Claudia Hulbert, Ian McBrearty +1
Slow earthquakes may trigger failure on neighboring locked faults that are stressed enough to break, and slow slip patterns may evolve before a nearby great earthquake. However, ev…
Machine Learning Reveals the State of Intermittent Frictional Dynamics in a Sheared Granular Fault
C. X. Ren, O. Dorostkar, B. Rouet-Leduc +5
Seismogenic plate boundaries are presumed to behave in a similar manner to a densely packed granular medium, where fault and blocks systems rapidly rearrange the distribution of fo…