| Pairwise Association of Seismic Arrivals with Convolutional Neural Networks IW McBrearty, AA Delorey, PA Johnson Seismological Research Letters, 2019 | 73 | 2019 |
| Earthquake phase association using a Bayesian Gaussian mixture model W Zhu, IW McBrearty, SM Mousavi, WL Ellsworth, GC Beroza Journal of Geophysical Research: Solid Earth 127 (5), e2021JB023249, 2022 | 63 | 2022 |
| Probing slow earthquakes with deep learning B Rouet‐Leduc, C Hulbert, IW McBrearty, PA Johnson Geophysical research letters 47 (4), e2019GL085870, 2020 | 52 | 2020 |
| Earthquake arrival association with backprojection and graph theory IW McBrearty, J Gomberg, AA Delorey, PA Johnson Bulletin of the Seismological Society of America 109 (6), 2510-2531, 2019 | 31 | 2019 |
| The Spatio‐temporal Evolution of Granular Microslip Precursors to Laboratory Earthquakes DT Trugman, IW McBrearty, DC Bolton, RA Guyer, C Marone, PA Johnson Geophysical Research Letters, e2020GL088404, 2020 | 21 | 2020 |
| Earthquake phase association with graph neural networks IW McBrearty, GC Beroza Bulletin of the Seismological Society of America, 2023 | 20 | 2023 |
| Basal seismicity of the Northeast Greenland Ice Stream IW McBrearty, LK Zoet, S Anandakrishnan Journal of Glaciology, 1-17, 2020 | 17 | 2020 |
| Earthquake location and magnitude estimation with graph neural networks IW McBrearty, GC Beroza 2022 IEEE International Conference on Image Processing (ICIP), 3858-3862, 2022 | 16 | 2022 |
| Discovery of a meta-stable Al–Sm phase with unknown stoichiometry using a genetic algorithm F Zhang, I McBrearty, RT Ott, E Park, MI Mendelev, MJ Kramer, CZ Wang, ... Scripta Materialia 81, 32-35, 2014 | 16 | 2014 |
| Investigating the influence of earthquake source complexity on back-projection images using convolutional neural networks M Corradini, IW McBrearty, DT Trugman, C Satriano, PA Johnson, ... Geophysical Journal International 229 (3), 1824-1839, 2022 | 2 | 2022 |
| Quakeflow: A scalable deep-learning-based earthquake monitoring workflow with cloud computing W Zhu, AB Hou, R Yang, A Datta, SM Mousavi, M Zhang, Y Park, ... AGU Fall Meeting Abstracts 2021, IN21A-07, 2021 | 1 | 2021 |
| High-Frequency Radiation and Earthquake Rupture Complexities: From Back Projection to a Machine Learning Approach. M Corradini, I McBrearty, BPG Rouet-Leduc, C Hulbert, C Satriano, ... Geophysical Research Abstracts 21, 2019 | 1 | 2019 |
| Patterns in seismic energy and earthquake hazard in Northern Chile C Hulbert, B Rouet-Leduc, IW McBrearty, PA Johnson AGU Fall Meeting Abstracts 2018, T43E-0456, 2018 | 1 | 2018 |
| Exploring Mayotte’s magmatic plumbing system using the variety and geometry of its seismicity L Retailleau, JM Saurel, IW McBrearty, GC Beroza, G Farge, A Lomax, ... EGU24, 2024 | | 2024 |
| Implementation of machine learning approaches to monitor pre-eruptive swarms at Piton de la Fournaise volcano M Menager, Z Duputel, L Retailleau, V Ferrazzini, I McBrearty EGU24, 2024 | | 2024 |
| Benchmarking seismic phase associators: Insights from synthetic scenarios JAP Huerta, J Münchmeyer, I McBrearty, C Sippl EGU24, 2024 | | 2024 |
| Global Earthquake Phase Association with Graph Neural Networks IW McBrearty, W Yeck, GC Beroza AGU23, 2023 | | 2023 |
| A Graph Neural Network Based Elastic Deformation Emulator for Arbitrarily Complex Magmatic Reservoirs T Wang, IW McBrearty, P Segall AGU23, 2023 | | 2023 |
| Machine Learning Methods of Association Applied to Dense Nodal Arrays C Pennington, IW McBrearty, Q Kong, WR Walter AGU23, 2023 | | 2023 |
| Machine Learning–Driven Analysis of Geophysical Signals I Poster W Zhu, J Münchmeyer, Y Li, IW McBrearty AGU23, 2023 | | 2023 |
Paul A. JohnsonLos Alamos National LaboratoryVerified email at lanl.gov
