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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 transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking
S. Mostafa Mousavi, William L. Ellsworth, Weiqiang Zhu, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 698

Showing 1-25 of 698 citing articles:

Scientific discovery in the age of artificial intelligence
Hanchen Wang, Tianfan Fu, Yuanqi Du, et al.
Nature (2023) Vol. 620, Iss. 7972, pp. 47-60
Closed Access | Times Cited: 678
Deep Learning for Geophysics: Current and Future Trends
Siwei Yu, Jianwei Ma
Reviews of Geophysics (2021) Vol. 59, Iss. 3
Open Access | Times Cited: 315
Deep-learning seismology
S. Mostafa Mousavi, Gregory C. Beroza
Science (2022) Vol. 377, Iss. 6607
Closed Access | Times Cited: 274
Physics‐Informed Neural Networks (PINNs) for Wave Propagation and Full Waveform Inversions
Majid Rasht‐Behesht, Christian Huber, Khemraj Shukla, et al.
Journal of Geophysical Research Solid Earth (2022) Vol. 127, Iss. 5
Open Access | Times Cited: 196
Deep learning for geological hazards analysis: Data, models, applications, and opportunities
Zhengjing Ma, Gang Mei
Earth-Science Reviews (2021) Vol. 223, pp. 103858-103858
Open Access | Times Cited: 193
A review of Earth Artificial Intelligence
Ziheng Sun, L. Sandoval, Robert Crystal‐Ornelas, et al.
Computers & Geosciences (2022) Vol. 159, pp. 105034-105034
Open Access | Times Cited: 168
Hybrid Deep-Learning Network for Rapid On-Site Peak Ground Velocity Prediction
Jingbao Zhu, Shanyou Li, Jindong Song
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-12
Closed Access | Times Cited: 120
Machine learning and earthquake forecasting—next steps
Gregory C. Beroza, Margarita Segou, S. Mostafa Mousavi
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 115
Which Picker Fits My Data? A Quantitative Evaluation of Deep Learning Based Seismic Pickers
Jannes Münchmeyer, Jack Woollam, Andreas Rietbrock, et al.
Journal of Geophysical Research Solid Earth (2022) Vol. 127, Iss. 1
Open Access | Times Cited: 112
Machine Learning in Earthquake Seismology
S. Mostafa Mousavi, Gregory C. Beroza
Annual Review of Earth and Planetary Sciences (2022) Vol. 51, Iss. 1, pp. 105-129
Open Access | Times Cited: 110
LOC-FLOW: An End-to-End Machine Learning-Based High-Precision Earthquake Location Workflow
Miao Zhang, Min Liu, Tian Feng, et al.
Seismological Research Letters (2022) Vol. 93, Iss. 5, pp. 2426-2438
Closed Access | Times Cited: 101
Earthquake Phase Association Using a Bayesian Gaussian Mixture Model
Weiqiang Zhu, Ian W. McBrearty, S. Mostafa Mousavi, et al.
Journal of Geophysical Research Solid Earth (2022) Vol. 127, Iss. 5
Open Access | Times Cited: 91
SeisBench—A Toolbox for Machine Learning in Seismology
Jack Woollam, Jannes Münchmeyer, Frederik Tilmann, et al.
Seismological Research Letters (2022) Vol. 93, Iss. 3, pp. 1695-1709
Open Access | Times Cited: 82
Machine learning in microseismic monitoring
Denis Anikiev, Claire Birnie, Umair bin Waheed, et al.
Earth-Science Reviews (2023) Vol. 239, pp. 104371-104371
Open Access | Times Cited: 60
Iterative integration of deep learning in hybrid Earth surface system modelling
Min Chen, Zhen Qian, Niklas Boers, et al.
Nature Reviews Earth & Environment (2023) Vol. 4, Iss. 8, pp. 568-581
Closed Access | Times Cited: 53
DiTing: A large-scale Chinese seismic benchmark dataset for artificial intelligence in seismology
Ming Zhao, Zhuowei Xiao, Shi Chen, et al.
Earthquake Science (2023) Vol. 36, Iss. 2, pp. 84-94
Open Access | Times Cited: 46
Sensing prior constraints in deep neural networks for solving exploration geophysical problems
Xinming Wu, Jianwei Ma, Xu Si, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 23
Open Access | Times Cited: 44
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: 20
Cascade and pre-slip models oversimplify the complexity of earthquake preparation in nature
Patricia Martínez‐Garzón, Piero Poli
Communications Earth & Environment (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 17
Towards the next generation of Geospatial Artificial Intelligence
Gengchen Mai, Yiqun Xie, Xiaowei Jia, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 136, pp. 104368-104368
Open Access | Times Cited: 1
Real-time determination of earthquake focal mechanism via deep learning
Wenhuan Kuang, Congcong Yuan, Jie Zhang
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 98
Machine Learning Improves Debris Flow Warning
Małgorzata Chmiel, Fabian Walter, Michaela Wenner, et al.
Geophysical Research Letters (2020) Vol. 48, Iss. 3
Open Access | Times Cited: 81
A Deep Learning Model for Earthquake Parameters Observation in IoT System-Based Earthquake Early Warning
Mohamed S. Abdalzaher, M. Sami Soliman, Sherif M. El-Hady, et al.
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 11, pp. 8412-8424
Closed Access | Times Cited: 79
Unsupervised 3-D Random Noise Attenuation Using Deep Skip Autoencoder
Liuqing Yang, Shoudong Wang, Xiaohong Chen, et al.
IEEE Transactions on Geoscience and Remote Sensing (2021) Vol. 60, pp. 1-16
Closed Access | Times Cited: 74
INSTANCE – the Italian seismic dataset for machine learning
Alberto Michelini, S. Cianetti, Sonja Gaviano, et al.
Earth system science data (2021) Vol. 13, Iss. 12, pp. 5509-5544
Open Access | Times Cited: 73
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