Physics‐Informed Deep Learning for Forward and Inverse Modeling of Inplane Crustal Deformation
Abstract Methods for modeling crustal deformation related to earthquakes and plate motions have been developed to incorporate complex crustal structures and multi‐fidelity observations. A machine learning approach called physics‐informed neural networks (PINNs), which can solve both forward and inve...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-03-01
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| Series: | Journal of Geophysical Research: Machine Learning and Computation |
| Online Access: | https://doi.org/10.1029/2024JH000474 |
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