| Machine learning predicts laboratory earthquakes B Rouet‐Leduc, C Hulbert, N Lubbers, K Barros, CJ Humphreys, ... Geophysical Research Letters 44 (18), 9276-9282, 2017 | 420 | 2017 |
| 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 | 157 | 2019 |
| Continuous chatter of the Cascadia subduction zone revealed by machine learning B Rouet-Leduc, C Hulbert, PA Johnson Nature Geoscience 12 (1), 75-79, 2019 | 127 | 2019 |
| 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 | 92 | 2018 |
| Laboratory earthquake forecasting: A machine learning competition PA Johnson, B Rouet-Leduc, LJ Pyrak-Nolte, GC Beroza, CJ Marone, ... Proceedings of the national academy of sciences 118 (5), e2011362118, 2021 | 79 | 2021 |
| Autonomous extraction of millimeter-scale deformation in InSAR time series using deep learning B Rouet-Leduc, R Jolivet, M Dalaison, PA Johnson, C Hulbert Nature communications 12 (1), 6480, 2021 | 67 | 2021 |
| Probing slow earthquakes with deep learning B Rouet‐Leduc, C Hulbert, IW McBrearty, PA Johnson Geophysical research letters 47 (4), e2019GL085870, 2020 | 54 | 2020 |
| 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 | 53 | 2019 |
| An exponential build-up in seismic energy suggests a months-long nucleation of slow slip in Cascadia C Hulbert, B Rouet-Leduc, R Jolivet, PA Johnson Nature communications 11 (1), 1-8, 2020 | 40* | 2020 |
| Machine learning reveals the state of intermittent frictional dynamics in a sheared granular fault CX Ren, O Dorostkar, B Rouet‐Leduc, C Hulbert, D Strebel, RA Guyer, ... Geophysical Research Letters 46 (13), 7395-7403, 2019 | 40 | 2019 |
| Machine learning and fault rupture: a review CX Ren, C Hulbert, PA Johnson, B Rouet-Leduc Advances in Geophysics 61, 57-107, 2020 | 33 | 2020 |
| Automatized convergence of optoelectronic simulations using active machine learning B Rouet-Leduc, C Hulbert, K Barros, T Lookman, CJ Humphreys Applied Physics Letters 111 (4), 2017 | 15 | 2017 |
| Subsurface stress criticality associated with fluid injection and determined using machine learning PA Johnson, CL Hulbert, B Rouet-Leduc US Patent 11,341,410, 2022 | 13 | 2022 |
| Failure prediction and estimation of failure parameters PA Johnson, CL Hulbert, B Rouet-Leduc US Patent 11,169,288, 2021 | 9 | 2021 |
| Mapping glacier basal sliding applying machine learning J Umlauft, CW Johnson, P Roux, DT Trugman, A Lecointre, A Walpersdorf, ... Journal of Geophysical Research: Earth Surface 128 (11), e2023JF007280, 2023 | 3 | 2023 |
| Tremor waveform extraction and automatic location with neural network interpretation C Hulbert, R Jolivet, B Gardonio, PA Johnson, CX Ren, B Rouet-Leduc IEEE Transactions on Geoscience and Remote Sensing 60, 1-9, 2022 | 3 | 2022 |
| Diffusion models for interferometric satellite aperture radar A Tuel, T Kerdreux, C Hulbert, B Rouet-Leduc arXiv preprint arXiv:2308.16847, 2023 | 2 | 2023 |
| Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer B Rouet-Leduc, C Hulbert Nature Communications 15 (1), 3801, 2024 | 1 | 2024 |
| Learning the low frequency earthquake daily intensity on the central San Andreas Fault C Johnson, C Hulbert, B Rouet-Leduc, P Johnson Authorea Preprints, 2022 | 1 | 2022 |
| A deep Learning approach for detecting transient deformation in InSAR B Rouet-Leduc, R Jolivet, M Dalaison, PA Johnson, C Hulbert AGU Fall Meeting Abstracts 2020, S056-07, 2020 | 1 | 2020 |
