96 citations as recorded by crossref.

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9. Recent Advances in Early Earthquake Magnitude Estimation by Using Machine Learning Algorithms: A Systematic Review A. Navarro-Rodríguez et al. https://doi.org/10.3390/app15073492
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25. EPick: Attention-based multi-scale UNet for earthquake detection and seismic phase picking W. Li et al. https://doi.org/10.3389/feart.2022.953007
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27. Evaluation of Seismic Artificial Intelligence with Uncertainty S. Myren et al. https://doi.org/10.1785/0220240444
28. Challenges and Opportunities of Machine Learning Earthquake Detection for Regional Monitoring S. Noel & M. West https://doi.org/10.1785/0120250021
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30. A machine learning modelling for the seismicity in the region of Greece from 2000 and thereafter A. Savvides et al. https://doi.org/10.1007/s42452-025-07012-2
31. Deep-learning seismology S. Mousavi & G. Beroza https://doi.org/10.1126/science.abm4470
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34. Cross-Regional Seismic Event Discrimination via Convolutional Neural Networks: Exploring Fine-Tuning and Ensemble Averaging V. Kasburg et al. https://doi.org/10.1785/0120230198
35. Divide and conquer: separating the two probabilities in seismic phase picking Y. Park et al. https://doi.org/10.1093/gji/ggaf333
36. Insights into the 2021 Arkalochori (Crete Island, southern Greece) foreshock swarm through an enhanced deep-learning seismic catalog F. Vallianatos et al. https://doi.org/10.1016/j.tecto.2025.231045
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38. MSEP-TFormer: a multitask source estimation parameter transformer network for earthquake monitoring X. Huang & Y. Zhang https://doi.org/10.1093/gji/ggaf453
39. Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning W. Zhu et al. https://doi.org/10.1038/s41467-023-43355-3
40. RPNet: Robust P-Wave First-Motion Polarity Determination Using Deep Learning J. Han et al. https://doi.org/10.1785/0220240384
41. EQCCT: A Production-Ready Earthquake Detection and Phase-Picking Method Using the Compact Convolutional Transformer O. Saad et al. https://doi.org/10.1109/TGRS.2023.3319440
42. A Novel Generative Adversarial Network for the Removal of Noise and Baseline Drift in Seismic Signals Y. Chen et al. https://doi.org/10.1109/TGRS.2024.3358901
43. Seis-PnSn: A Global Million-Scale Benchmark Data Set of Pn and Sn Seismic Phases for Deep Learning H. Kong et al. https://doi.org/10.1785/0220230379
44. SeisAug: A data augmentation python toolkit D. Pragnath et al. https://doi.org/10.1016/j.acags.2025.100232
45. SeismoDual: A dual-domain deep learning framework for robust seismic phase picking K. Tang & K. Chen https://doi.org/10.1016/j.cageo.2025.106080
46. Seismology in the cloud: guidance for the individual researcher Z. Krauss et al. https://doi.org/10.26443/seismica.v2i2.979
47. Seismicity catalogue of the entire Chilean margin (18 to 56° S) from an automated approach M. Riedel-Hornig et al. https://doi.org/10.5194/essd-18-1-2026
48. Ojos del Salado: how active is this sleeping giant? L. Murray-Bergquist et al. https://doi.org/10.1093/gji/ggag108
49. Spatio-temporal deep networks with feature disentangling for advancing earthquake monitoring F. Meng et al. https://doi.org/10.1016/j.cageo.2025.105974
50. Machine Learning Applications in Seismology K. Jia & S. Zhou https://doi.org/10.3390/app14177857
51. CREDIT-X1local: A reference dataset for machine learning seismology from ChinArray in Southwest China L. Li et al. https://doi.org/10.1016/j.eqs.2024.01.018
52. A Theory-Guided Encoder-Decoder model for short- and Long-Horizon seismic response prediction of nonlinear Single-Degree-of-Freedom systems Z. Pan et al. https://doi.org/10.1016/j.compstruc.2025.107719
53. En echelon faults reactivated by wastewater disposal near Musreau Lake, Alberta R. Schultz et al. https://doi.org/10.1093/gji/ggad226
54. Learning source, path and site effects: CNN-based on-site intensity prediction for earthquake early warning H. Zhang et al. https://doi.org/10.1093/gji/ggac325
55. EQConvMixer: A Deep Learning Approach for Earthquake Location From Single-Station Waveforms H. Elsayed et al. https://doi.org/10.1109/LGRS.2023.3312324
56. OpenSWI: a massive-scale benchmark dataset for surface wave dispersion curve inversion F. Liu et al. https://doi.org/10.5194/essd-18-2769-2026
57. Deep Learning and Machine Learning Applied to the Detection and Classification of Volcano-Seismic Events at Piton de la Fournaise Volcano R. Machacca et al. https://doi.org/10.1007/s00024-025-03809-9
58. Better Together: Ensemble Learning for Earthquake Detection and Phase Picking C. Yuan et al. https://doi.org/10.1109/TGRS.2023.3320148
59. Deep learning based earthquake and vehicle detection algorithm D. Ertuncay et al. https://doi.org/10.1007/s10950-024-10267-8
60. Application of a Deep Learning Phase Picker to Improve the Performance of Deep Borehole Seismic Data Analysis Y. Hong & D. Sheen https://doi.org/10.9719/EEG.2024.57.6.701
61. Detection of mining-induced microseismicity through a deep convolutional neural network S. Vafaei Shoushtari et al. https://doi.org/10.1016/j.jappgeo.2025.106069
62. CubeNet: Array-Based Seismic Phase Picking with Deep Learning G. Chen & J. Li https://doi.org/10.1785/0220220147
63. (Re)Discovering the Seismicity of Antarctica: A New Seismic Catalog for the Southernmost Continent A. Peña Castro et al. https://doi.org/10.1785/0220240076
64. Intelligent solutions for earthquake data analysis and prediction for future smart cities B. Dey et al. https://doi.org/10.1016/j.cie.2022.108368
65. Machine Learning in Earthquake Seismology S. Mousavi & G. Beroza https://doi.org/10.1146/annurev-earth-071822-100323
66. A multitask encoder–decoder to separate earthquake and ambient noise signal in seismograms J. Yin et al. https://doi.org/10.1093/gji/ggac290
67. GTUNE: An Assembled Global Seismic Dataset of Underground Nuclear Test Blasts L. Barama et al. https://doi.org/10.1785/0220220036
68. Impact of machine-learning phase picking on seismic tomography at Popocatépetl Volcano, Mexico K. Bernal-Manzanilla & M. Calò https://doi.org/10.1016/j.jsames.2026.105996
69. Picking Induced Seismicity with Deep Learning (piSDL) J. Heuel et al. https://doi.org/10.26443/seismica.v4i2.1579
70. From flat to steep subduction: the South Peru margin imaged by a new high-density seismic catalogue C. Chalumeau et al. https://doi.org/10.1093/gji/ggag119
71. Comparing and integrating artificial intelligence and similarity search detection techniques: application to seismic sequences in Southern Italy F. Scotto di Uccio et al. https://doi.org/10.1093/gji/ggac487
72. Test-Time Augmentations and Quality Controls for Improving Regional Seismic Phase Picking B. Han et al. https://doi.org/10.3390/s25237238
73. Deep learning models for regional phase detection on seismic stations in Northern Europe and the European Arctic E. Myklebust & A. Köhler https://doi.org/10.1093/gji/ggae298
74. Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes N. D’Angelo et al. https://doi.org/10.1080/10618600.2023.2206441
75. Predicting peak ground acceleration using the ConvMixer network M. Mohammed et al. https://doi.org/10.1016/j.eqs.2024.11.005
76. DiTing: A large-scale Chinese seismic benchmark dataset for artificial intelligence in seismology M. Zhao et al. https://doi.org/10.1016/j.eqs.2022.01.022
77. Ground-Shaking Intensity Prediction for Onsite Earthquake Early Warning Using Deep Learning M. Jiang et al. https://doi.org/10.1785/0220230263
78. A Robust and Rapid Grid-Based Machine Learning Approach for Inside and Off-Network Earthquakes Classification in Dynamically Changing Seismic Networks D. Annunziata et al. https://doi.org/10.1785/0220240173
79. Denoising Seismograms in the Time Domain Using a Deep Learning Model C. Chai et al. https://doi.org/10.1785/0120250143
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81. The magmatic web beneath Hawai‘i J. Wilding et al. https://doi.org/10.1126/science.ade5755
82. Earthquake monitoring using deep learning with a case study of the Kahramanmaras Turkey earthquake aftershock sequence W. Li et al. https://doi.org/10.5194/se-15-197-2024
83. Comparison of Deep Learning Techniques for the Investigation of a Seismic Sequence: An Application to the 2019, Mw 4.5 Mugello (Italy) Earthquake S. Cianetti et al. https://doi.org/10.1029/2021JB023405
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85. A New High-Resolution Seismic Catalog for Southwestern Australia (2020–2025) and Analysis of Long-Term Clustering Behavior R. Pickle et al. https://doi.org/10.1785/0220250308
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87. Advances in geophysical forensic event monitoring M. Pasyanos et al. https://doi.org/10.1038/s43017-025-00702-w
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