43 citations as recorded by crossref.

1. Convolutional neural networks with SegNet architecture applied to three-dimensional tomography of subsurface electrical resistivity: CNN-3D-ERT M. Vu & A. Jardani 10.1093/gji/ggab024
2. Seismic savanna: machine learning for classifying wildlife and behaviours using ground‐based vibration field recordings A. Szenicer et al. 10.1002/rse2.242
3. High-frequency wavefield extrapolation using the Fourier neural operator C. Song & Y. Wang 10.1093/jge/gxac016
4. High-Precision Intelligence Denoising of Potential Field Data Based on RevU-Net Z. Zhou et al. 10.1109/LGRS.2023.3241295
5. Time Domain Reflectometry Waveform Interpretation With Convolutional Neural Networks Z. Wang et al. 10.1029/2022WR033895
6. Physics-informed neural networks for transcranial ultrasound wave propagation L. Wang et al. 10.1016/j.ultras.2023.107026
7. Approximation of modal wavenumbers and group speeds in an oceanic waveguide using a neural network A. Varon et al. 10.1121/10.0019704
8. Seismic Wave Propagation and Inversion with Neural Operators Y. Yang et al. 10.1785/0320210026
9. Simulating Multicomponent Elastic Seismic Wavefield Using Deep Learning C. Song et al. 10.1109/LGRS.2023.3250522
10. Deep learning, machine learning and internet of things in geophysical engineering applications: An overview K. Dimililer et al. 10.1016/j.micpro.2020.103613
11. Accelerating Bayesian microseismic event location with deep learning A. Spurio Mancini et al. 10.5194/se-12-1683-2021
12. Rapid Seismic Waveform Modeling and Inversion With Neural Operators Y. Yang et al. 10.1109/TGRS.2023.3264210
13. Multi-task neural network in hydrological tomography to map the transmissivity and storativity simultaneously: HT-XNET M. Vu & A. Jardani 10.1016/j.jhydrol.2022.128167
14. Deep neural network reducing numerical dispersion for post-processing of seismic modeling results K. Gadylshina et al. 10.18303/2619-1563-2022-1-99
15. Solving the frequency-domain acoustic VTI wave equation using physics-informed neural networks C. Song et al. 10.1093/gji/ggab010
16. A versatile framework to solve the Helmholtz equation using physics-informed neural networks C. Song et al. 10.1093/gji/ggab434
17. Machine learning‐accelerated gradient‐based Markov chain Monte Carlo inversion applied to electrical resistivity tomography M. Aleardi et al. 10.1002/nsg.12211
18. Bayesian Geophysical Inversion Using Invertible Neural Networks X. Zhang & A. Curtis 10.1029/2021JB022320
19. Removing Time Dispersion from Elastic Wave Modeling with the pix2pix Algorithm Based on cGAN T. Xu et al. 10.3390/rs15123120
20. Physics‐Informed Neural Networks (PINNs) for Wave Propagation and Full Waveform Inversions M. Rasht‐Behesht et al. 10.1029/2021JB023120
21. Machine Learning in Earthquake Seismology S. Mousavi & G. Beroza 10.1146/annurev-earth-071822-100323
22. Wavefield Reconstruction Inversion via Physics-Informed Neural Networks C. Song & T. Alkhalifah 10.1109/TGRS.2021.3123122
23. A Three-Dimensional Geological Structure Modeling Framework and Its Application in Machine Learning S. Wang et al. 10.1007/s11004-022-10027-9
24. Small-data-driven fast seismic simulations for complex media using physics-informed Fourier neural operators W. Wei & L. Fu 10.1190/geo2021-0573.1
25. Numerical dispersion mitigation neural network for seismic modeling K. Gadylshin et al. 10.1190/geo2021-0242.1
26. Accelerating 2D and 3D frequency-domain seismic wave modeling through interpolating frequency-domain wavefields by deep learning W. Cao et al. 10.1190/geo2021-0435.1
27. Multitasking neural network to jointly map discrete fracture structures and matrix transmissivity by inverting hydraulic data acquired in 2D fractured aquifers. XNET-fracture M. Vu & A. Jardani 10.1016/j.advwatres.2023.104463
28. Nonlinear seismic inversion by physics-informed Caianiello convolutional neural networks for overpressure prediction of source rocks in the offshore Xihu depression, East China Y. Cheng & L. Fu 10.1016/j.petrol.2022.110654
29. Predicting transmission loss in underwater acoustics using convolutional recurrent autoencoder network W. Mallik et al. 10.1121/10.0013894
30. Ground-Motion Evaluation of Hybrid Seismic Velocity Models R. Ajala & P. Persaud 10.1785/0320220022
31. Data-driven model discovery for plasma turbulence modelling I. Abramovic et al. 10.1017/S0022377822001192
32. Deep-neural-networks-based approaches for Biot–squirt model in rock physics F. Xiong et al. 10.1007/s11600-022-00740-8
33. Uncertainty Quantification in Intelligent-Based Electrical Resistivity Tomography Image Reconstruction With Monte Carlo Dropout Strategy L. Xixi et al. 10.1109/TGRS.2023.3262835
34. Efficient low-fidelity aeroacoustic permanence calculation of propellers F. Yunus et al. 10.1016/j.ast.2022.107438
35. Instantaneous Physics‐Based Ground Motion Maps Using Reduced‐Order Modeling J. Rekoske et al. 10.1029/2023JB026975
36. Multi-frequency wavefield modeling of acoustic VTI wave equation using physics informed neural networks A. Sandhu et al. 10.3389/feart.2023.1227828
37. DEEP LEARNING-BASED NUMERICAL DISPERSION MITIGIATION IN SEISMIC MODELLING K. Gadylshina et al. 10.33764/2618-981X-2021-2-2-17-25
38. Deep learning for fast simulation of seismic waves in complex media B. Moseley et al. 10.5194/se-11-1527-2020
39. A 3D complexity-adaptive approach to explore sparsity in elastic wave propagation C. Haindl et al. 10.1190/geo2020-0490.1
40. Deep Learning for 3-D Inversion of Gravity Data L. Zhang et al. 10.1109/TGRS.2021.3110606
41. Data‐Driven Design of Wave‐Propagation Models for Shale‐Oil Reservoirs Based on Machine Learning F. Xiong et al. 10.1029/2021JB022665
42. Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations B. Moseley et al. 10.1007/s10444-023-10065-9
43. Deep learning for fast simulation of seismic waves in complex media B. Moseley et al. 10.5194/se-11-1527-2020