Ian McBrearty

Ian McBrearty

Stanford University

H-index: 9

North America-United States

About Ian McBrearty

Ian McBrearty, With an exceptional h-index of 9 and a recent h-index of 9 (since 2020), a distinguished researcher at Stanford University, specializes in the field of Seismology.

His recent articles reflect a diverse array of research interests and contributions to the field:

Implementation of machine learning approaches to monitor pre-eruptive swarms at Piton de la Fournaise volcano

Benchmarking seismic phase associators: Insights from synthetic scenarios

Earthquake phase association with graph neural networks

Earthquake location and magnitude estimation with graph neural networks

Investigating the influence of earthquake source complexity on back-projection images using convolutional neural networks

Earthquake phase association using a Bayesian Gaussian mixture model

Quakeflow: A scalable deep-learning-based earthquake monitoring workflow with cloud computing

Probing slow earthquakes with deep learning

Ian McBrearty Information

University

Position

Department of Geophysics

Citations(all)

283

Citations(since 2020)

275

Cited By

56

hIndex(all)

9

hIndex(since 2020)

9

i10Index(all)

9

i10Index(since 2020)

9

Email

University Profile Page

Google Scholar

Ian McBrearty Skills & Research Interests

Seismology

Top articles of Ian McBrearty

Implementation of machine learning approaches to monitor pre-eruptive swarms at Piton de la Fournaise volcano

2024/3/7

Zacharie Duputel
Zacharie Duputel

H-Index: 22

Ian Mcbrearty
Ian Mcbrearty

H-Index: 4

Benchmarking seismic phase associators: Insights from synthetic scenarios

2024/3/7

Ian Mcbrearty
Ian Mcbrearty

H-Index: 4

Earthquake phase association with graph neural networks

Bulletin of the Seismological Society of America

2023/4/1

Earthquake location and magnitude estimation with graph neural networks

2022/10/16

Investigating the influence of earthquake source complexity on back-projection images using convolutional neural networks

Geophysical Journal International

2022/6

Earthquake phase association using a Bayesian Gaussian mixture model

Journal of Geophysical Research: Solid Earth

2022/5

Quakeflow: A scalable deep-learning-based earthquake monitoring workflow with cloud computing

AGU Fall Meeting Abstracts

2021/12

Probing slow earthquakes with deep learning

Geophysical research letters

2020/2/28

The Spatio‐temporal Evolution of Granular Microslip Precursors to Laboratory Earthquakes

Geophysical Research Letters

2020

Basal seismicity of the Northeast Greenland Ice Stream

Journal of Glaciology

2020/6

See List of Professors in Ian McBrearty University(Stanford University)

Co-Authors

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