Suivre
David C. Bolton
David C. Bolton
Adresse e-mail validée de austin.utexas.edu
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Citée par
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Année
Similarity of fast and slow earthquakes illuminated by machine learning
C Hulbert, B Rouet-Leduc, PA Johnson, CX Ren, J Rivière, DC Bolton, ...
Nature Geoscience 12 (1), 69-74, 2019
1452019
DeepDetect: A cascaded region-based densely connected network for seismic event detection
Y Wu, Y Lin, Z Zhou, DC Bolton, J Liu, P Johnson
IEEE Transactions on Geoscience and Remote Sensing 57 (1), 62-75, 2018
1342018
Estimating fault friction from seismic signals in the laboratory
B Rouet‐Leduc, C Hulbert, DC Bolton, CX Ren, J Riviere, C Marone, ...
Geophysical Research Letters 45 (3), 1321-1329, 2018
872018
Characterizing acoustic signals and searching for precursors during the laboratory seismic cycle using unsupervised machine learning
DC Bolton, P Shokouhi, B Rouet‐Leduc, C Hulbert, J Rivière, C Marone, ...
Seismological Research Letters 90 (3), 1088-1098, 2019
512019
Earthquake catalog‐based machine learning identification of laboratory fault states and the effects of magnitude of completeness
N Lubbers, DC Bolton, J Mohd‐Yusof, C Marone, K Barros, PA Johnson
Geophysical Research Letters 45 (24), 13,269-13,276, 2018
502018
Acoustic energy release during the laboratory seismic cycle: Insights on laboratory earthquake precursors and prediction
DC Bolton, S Shreedharan, J Rivière, C Marone
Journal of Geophysical Research: Solid Earth 125 (8), e2019JB018975, 2020
422020
Preseismic fault creep and elastic wave amplitude precursors scale with lab earthquake magnitude for the continuum of tectonic failure modes
S Shreedharan, DC Bolton, J Rivière, C Marone
Geophysical Research Letters 47 (8), e2020GL086986, 2020
372020
Competition between preslip and deviatoric stress modulates precursors for laboratory earthquakes
S Shreedharan, DC Bolton, J Rivière, C Marone
Earth and Planetary Science Letters 553, 116623, 2021
282021
Machine learning predicts the timing and shear stress evolution of lab earthquakes using active seismic monitoring of fault zone processes
S Shreedharan, DC Bolton, J Rivière, C Marone
Journal of Geophysical Research: Solid Earth 126 (7), e2020JB021588, 2021
222021
The spatiotemporal evolution of granular microslip precursors to laboratory earthquakes
DT Trugman, IW McBrearty, DC Bolton, RA Guyer, C Marone, PA Johnson
Geophysical Research Letters 47 (16), e2020GL088404, 2020
222020
Attention network forecasts time‐to‐failure in laboratory shear experiments
H Jasperson, DC Bolton, P Johnson, R Guyer, C Marone, MV de Hoop
Journal of Geophysical Research: Solid Earth 126 (11), e2021JB022195, 2021
192021
Frequency‐magnitude statistics of laboratory foreshocks vary with shear velocity, fault slip rate, and shear stress
DC Bolton, S Shreedharan, J Rivière, C Marone
Journal of Geophysical Research: Solid Earth 126 (11), e2021JB022175, 2021
142021
The high‐frequency signature of slow and fast laboratory earthquakes
DC Bolton, S Shreedharan, GC McLaskey, J Rivière, P Shokouhi, ...
Journal of Geophysical Research: Solid Earth 127 (6), e2022JB024170, 2022
112022
Unsupervised classification of acoustic emissions from catalogs and fault time-to-failure prediction
HA Jasperson, DC Bolton, PA Johnson, C Marone, M Dehoop
AGU Fall Meeting Abstracts 2019, S53A-06, 2019
112019
Cascaded contextual region-based convolutional neural network for event detection from time series signals: A seismic application
Y Wu, Y Lin, Z Zhou, DC Bolton, J Liu, P Johnson
arXiv preprint arXiv:1709.07943 17, 2017
82017
Foreshock properties illuminate nucleation processes of slow and fast laboratory earthquakes
DC Bolton, C Marone, D Saffer, DT Trugman
Nature communications 14 (1), 3859, 2023
62023
Estimating the physical state of a laboratory slow slipping fault from seismic signals
C Hulbert, B Rouet-Leduc, CX Ren, J Riviere, DC Bolton, C Marone, ...
arXiv preprint arXiv:1801.07806, 2018
42018
Cascaded region-based densely connected network for event detection: A seismic application
Y Wu, Y Lin, Z Zhou, DC Bolton, J Liu, P Johnson
arXiv preprint arXiv:1709.07943, 2017
32017
Machine learning predicts the timing and shear stress evolution of lab earthquakes using active seismic monitoring of fault zone processes
S Shreedharan, DC Bolton, J Rivière, C Marone
Authorea Preprints, 2022
22022
Fault friction constitutive law derived from continuous acoustic emissions by machine learning
B Rouet-Leduc, C Hulbert, DC Bolton, CX Ren, C Marone, RA Guyer, ...
arXiv preprint arXiv:1710.04172, 2017
22017
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