| Machine Learning Predicts Laboratory Earthquakes B Rouet-Leduc, C Hulbert, N Lubbers, K Barros, C Humphreys, ... Geophysical Research Letters, 2017 | 420 | 2017 |
| Similarity of fast and slow earthquakes illuminated by machine learning C Hulbert, B Rouet-Leduc, CX Ren, J Riviere, DC Bolton, C Marone, ... Nature Geoscience, 2018 | 157 | 2018 |
| Continuous chatter of the Cascadia subduction zone revealed by machine learning B Rouet-Leduc, C Hulbert, PA Johnson Nature Geoscience, 2018 | 127 | 2018 |
| 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, 2018 | 91 | 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, 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 |
| Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning B Rouet-Leduc, K Barros, T Lookman, CJ Humphreys Scientific Reports 6, 24862, 2016 | 52 | 2016 |
| Machine learning reveals the seismic signature of eruptive behavior at Piton de la Fournaise volcano CX Ren, A Peltier, V Ferrazzini, B Rouet‐Leduc, PA Johnson, F Brenguier Geophysical Research Letters 47 (3), e2019GL085523, 2020 | 51 | 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 |
| Nanocathodoluminescence reveals mitigation of the stark shift in InGaN quantum wells by Si doping JT Griffiths, S Zhang, B Rouet-Leduc, WY Fu, A Bao, D Zhu, DJ Wallis, ... Nano letters 15 (11), 7639-7643, 2015 | 40 | 2015 |
| 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), 4139, 2020 | 35 | 2020 |
| 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 |
| Distributed database kriging for adaptive sampling (D2KAS) D Roehm, RS Pavel, K Barros, B Rouet-Leduc, AL McPherson, ... Computer Physics Communications 192, 138-147, 2015 | 28 | 2015 |
| Instantaneous tracking of earthquake growth with elastogravity signals A Licciardi, Q Bletery, B Rouet-Leduc, JP Ampuero, K Juhel Nature 606 (7913), 319-324, 2022 | 27 | 2022 |
| Spatial adaptive sampling in multiscale simulation B Rouet-Leduc, K Barros, E Cieren, V Elango, C Junghans, T Lookman, ... Computer Physics Communications 185 (7), 1857-1864, 2014 | 27 | 2014 |
| 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 | 16 | 2017 |
| Analysis of defect-related inhomogeneous electroluminescence in InGaN/GaN QW LEDs CX Ren, B Rouet-Leduc, JT Griffiths, E Bohacek, MJ Wallace, ... Superlattices and Microstructures 99, 118-124, 2016 | 15 | 2016 |
| 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 |
Claudia HulbertGeolabe在 geolabe.com 的电子邮件经过验证
