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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Earthquake Phase Association with Graph Neural Networks
Ian W. McBrearty, Gregory C. Beroza
Bulletin of the Seismological Society of America (2023) Vol. 113, Iss. 2, pp. 524-547
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Recent advances in earthquake seismology using machine learning
Hisahiko Kubo, Makoto Naoi, Masayuki Kano
Earth Planets and Space (2024) Vol. 76, Iss. 1
Open Access | Times Cited: 21
PyOcto: A high-throughput seismic phase associator
Jannes Münchmeyer
Seismica (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 13
An all-in-one seismic phase picking, location, and association network for multi-task multi-station earthquake monitoring
Xu Si, Xinming Wu, Zefeng Li, et al.
Communications Earth & Environment (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 12
Emerging technologies and supporting tools for earthquake disaster management: A perspective, challenges, and future directions
Mohamed S. Abdalzaher, Moez Krichen, Francisco Falcone
Progress in Disaster Science (2024) Vol. 23, pp. 100347-100347
Open Access | Times Cited: 6
Phase Neural Operator for Multi‐Station Picking of Seismic Arrivals
Hongyu Sun, Zachary E. Ross, Weiqiang Zhu, et al.
Geophysical Research Letters (2023) Vol. 50, Iss. 24
Open Access | Times Cited: 15
CREDIT-X1local: A reference dataset for machine learning seismology from ChinArray in Southwest China
Lu Li, Weitao Wang, Ziye Yu, et al.
Earthquake Science (2024) Vol. 37, Iss. 2, pp. 139-157
Open Access | Times Cited: 5
Unveiling midcrustal seismic activity at the front of the Bolivian altiplano, Cochabamba region
Gonzalo A. Fernandez, Benoît Derode, Laurent Bollinger, et al.
Seismica (2025) Vol. 4, Iss. 1
Open Access
A Comparison of Machine Learning Methods of Association Tested on Dense Nodal Arrays
Colin Pennington, Ian W. McBrearty, Qingkai Kong, et al.
Seismological Research Letters (2025)
Closed Access
Dense Seismic Recordings of the 2023 Kahramanmaraş Earthquake Sequence in Southeastern Türkiye
E. Zor, Zhigang Peng, M. Ergin, et al.
Seismological Research Letters (2025)
Closed Access
SeisAug: A Data Augmentation Python Toolkit
D. Pragnath, G. Srijayanthi, Santosh Kumar, et al.
Applied Computing and Geosciences (2025), pp. 100232-100232
Open Access
Machine Learning-Based Rapid Epicentral Distance Estimation from a Single Station
Jingbao Zhu, Wentao Sun, Xueying Zhou, et al.
Bulletin of the Seismological Society of America (2024) Vol. 114, Iss. 3, pp. 1507-1522
Closed Access | Times Cited: 4
PEGSGraph: A Graph Neural Network for Fast Earthquake Characterization Based on Prompt ElastoGravity Signals
Céline Hourcade, Kévin Juhel, Quentin Blétery
Journal of Geophysical Research Machine Learning and Computation (2025) Vol. 2, Iss. 1
Open Access
Low-frequency tremor-like episodes before the 2023 MW 7.8 Türkiye earthquake linked to cement quarrying
Zahra Zali, Patricia Martínez‐Garzón, Grzegorz Kwiatek, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
EQGraphNet: Advancing single-station earthquake magnitude estimation via deep graph networks with residual connections
Zhiguo Wang, Ziwei Chen, Huai Zhang
Artificial Intelligence in Geosciences (2024) Vol. 5, pp. 100089-100089
Open Access | Times Cited: 3
A Specific Earthquake Processing Workflow for Studying Long‐Lived, Explosive Volcanic Eruptions With Application to the 2008 Okmok Volcano, Alaska, Eruption
Ricardo Garza‐Girón, E. E. Brodsky, Zack Spica, et al.
Journal of Geophysical Research Solid Earth (2023) Vol. 128, Iss. 5
Open Access | Times Cited: 7
Next Generation Seismic Source Detection by Computer Vision: Untangling the Complexity of the 2016 Kaikōura Earthquake Sequence
Fengzhou Tan, Honn Kao, Kwang Moo Yi, et al.
Journal of Geophysical Research Solid Earth (2024) Vol. 129, Iss. 5
Open Access | Times Cited: 1
DMLoc: Automatic Microseismic Locating Workflow Based on Deep Learning and Waveform Migration
Yizhuo Liu, Jing Zheng, Ruijia Wang, et al.
Seismological Research Letters (2024) Vol. 95, Iss. 5, pp. 2997-3007
Closed Access | Times Cited: 1
Colombian Seismic Monitoring Using Advanced Machine-Learning Algorithms
E. Castillo, Daniel Siervo, G. A. Prieto
Seismological Research Letters (2024) Vol. 95, Iss. 5, pp. 2971-2985
Closed Access | Times Cited: 1
Deep Learning for Deep Earthquakes: Insights from OBS Observations of the Tonga Subduction Zone
Ziyi Xi, S. Shawn Wei, Weiqiang Zhu, et al.
Geophysical Journal International (2024) Vol. 238, Iss. 2, pp. 1073-1088
Open Access | Times Cited: 1
Universal neural networks for real-time earthquake early warning trained with generalized earthquakes
Xiong Zhang, Miao Zhang
Communications Earth & Environment (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 1
A Deep-Learning Phase Picker with Calibrated Bayesian-Derived Uncertainties for Earthquakes in the Yellowstone Volcanic Region
Alysha D. Armstrong, Zachary Claerhout, Ben Baker, et al.
Bulletin of the Seismological Society of America (2023) Vol. 113, Iss. 6, pp. 2323-2344
Closed Access | Times Cited: 2
GRAPES: Earthquake Early Warning by Passing Seismic Vectors Through the Grapevine
Timothy Clements, E. S. Cochran, A. Baltay, et al.
Geophysical Research Letters (2024) Vol. 51, Iss. 9
Open Access
Performance of AI-Based Phase Picking and Event Association Methods after the Large 2023 Mw 7.8 and 7.6 Türkiye Doublet
Dirk Becker, Ian W. McBrearty, Gregory C. Beroza, et al.
Bulletin of the Seismological Society of America (2024) Vol. 114, Iss. 5, pp. 2457-2473
Closed Access
Seis-PnSn: A Global Million-Scale Benchmark Data Set of Pn and Sn Seismic Phases for Deep Learning
Hua Kong, Zhuowei Xiao, Yan Lü, et al.
Seismological Research Letters (2024) Vol. 95, Iss. 6, pp. 3746-3760
Closed Access
Deep Learning Forecasts Caldera Collapse Events at Kı̄lauea Volcano
Ian W. McBrearty, P. Segall
Journal of Geophysical Research Solid Earth (2024) Vol. 129, Iss. 8
Open Access
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