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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:

Machine learning and fault rupture: A review
Christopher X. Ren, Claudia Hulbert, Paul A. Johnson, et al.
Advances in geophysics (2020), pp. 57-107
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

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: 62
Predicting fault slip via transfer learning
Kun Wang, Christopher Johnson, Kane C. Bennett, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 47
Inclusion of data uncertainty in machine learning and its application in geodetic data science, with case studies for the prediction of Earth orientation parameters and GNSS station coordinate time series
Mostafa Kiani Shahvandi, Benedikt Soja
Advances in Space Research (2022) Vol. 70, Iss. 3, pp. 563-575
Open Access | Times Cited: 32
Instantaneous tracking of earthquake growth with elastogravity signals
Andrea Licciardi, Quentin Blétery, Bertrand Rouet‐Leduc, et al.
Nature (2022) Vol. 606, Iss. 7913, pp. 319-324
Open Access | Times Cited: 30
Explainable machine learning for labquake prediction using catalog-driven features
Sadegh Karimpouli, Danu Caus, Harsh Grover, et al.
Earth and Planetary Science Letters (2023) Vol. 622, pp. 118383-118383
Open Access | Times Cited: 17
Unsupervised clustering of catalogue-driven features for characterizing temporal evolution of labquake stress
Sadegh Karimpouli, Grzegorz Kwiatek, Patricia Martínez‐Garzón, et al.
Geophysical Journal International (2024) Vol. 237, Iss. 2, pp. 755-771
Open Access | Times Cited: 7
Automatic speech recognition predicts contemporaneous earthquake fault displacement
Christopher Johnson, Kun Wang, Paul A. Johnson
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A Machine Learning Approach Using Recurrent Neural Networks (RNNs)
Tae-hoon UHMB, Yohei Hamada, Takehiro Hirose
Applied Computing and Geosciences (2025), pp. 100231-100231
Open Access
Application of artificial intelligence technology in the study of anthropogenic earthquakes: a review
Jingwei Li, Hongyu Zhai, Changsheng Jiang, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 5
Open Access
Innovative Approaches for Earthquake Estimation Using AI and ML Techniques
Sachin Upadhye, Shanmugasundaram Senathipathi, Krishna Kumar Shreedharan, et al.
Advances in computational intelligence and robotics book series (2025), pp. 203-226
Closed Access
A multitask encoder–decoder to separate earthquake and ambient noise signal in seismograms
Jiuxun Yin, Marine Denolle, Bing He
Geophysical Journal International (2022) Vol. 231, Iss. 3, pp. 1806-1822
Open Access | Times Cited: 11
Global Nuclear Explosion Discrimination Using a Convolutional Neural Network
Louisa Barama, Jesse Williams, A. V. Newman, et al.
Geophysical Research Letters (2023) Vol. 50, Iss. 17
Open Access | Times Cited: 5
Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments
Prabhav Borate, Jacques Rivière, Samson Marty, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
A Deep-Learning P-Wave Arrival Picker for Laboratory Acoustic Emissions: Model Training and Its Performance
Tian Guo, Tiziana Vanorio, Jihui Ding
Rock Mechanics and Rock Engineering (2024)
Closed Access | Times Cited: 1
Nucleation and Evolution of Sliding in Continental Fault Zones under the Action of Natural and Man-Made Factors: A State-of-the-Art Review
G. G. Kocharyan
Izvestiya Physics of the Solid Earth (2021) Vol. 57, Iss. 4, pp. 439-473
Closed Access | Times Cited: 10
Empowering English language learning and mental health using AI and Big data
Jingjing Long, Jiaxin Lin
Education and Information Technologies (2023) Vol. 29, Iss. 10, pp. 12703-12734
Closed Access | Times Cited: 3
Tremor Waveform Extraction and Automatic Location With Neural Network Interpretation
Claudia Hulbert, Romain Jolivet, Blandine Gardonio, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-9
Open Access | Times Cited: 5
Can Deep Learning Predict Complete Ruptures in Numerical Megathrust Faults?
D. G. Blank, Julia K. Morgan
Geophysical Research Letters (2021) Vol. 48, Iss. 18
Closed Access | Times Cited: 5
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
Deep learning‐based inversion with discrete cosine transform discretization for two‐dimensional basement relief imaging of sedimentary basins from observed gravity anomalies
Arka Roy, Yunus Levent Ekinci, Çağlayan Balkaya, et al.
Geophysical Prospecting (2024)
Open Access
Earthquake Prediction for Turkey: Ensemble Learning Approach
A. Tekín, Cem Sarı
Lecture notes in networks and systems (2024), pp. 203-212
Closed Access
Probing Seismogenic Faults with Machine Learning
Paul A. Johnson, Christopher Johnson
2022 IEEE International Conference on Image Processing (ICIP) (2022), pp. 2371-2375
Closed Access | Times Cited: 2
Global Nuclear Blast Discrimination using a Convolutional Neural Network
Louisa Barama, Jesse Williams, A. V. Newman, et al.
(2022)
Open Access | Times Cited: 1
Predicting Fault Slip via Transfer Learning
Kun Wang, Christopher Johnson, Kane C. Bennett, et al.
Research Square (Research Square) (2021)
Open Access | Times Cited: 1
Peculiarities of Dynamic Slip Nucleation in a Thin Granular Layer
А. А. Остапчук, G. G. Kocharyan, К. Г. Морозова, et al.
Izvestiya Physics of the Solid Earth (2021) Vol. 57, Iss. 5, pp. 659-670
Closed Access | Times Cited: 1
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