Physics‐Informed Deep Learning for Forward and Inverse Modeling of Inplane Crustal Deformation

• Published in: Journal of geophysical research. Machine learning and computation Vol. 2; no. 1
• Main Authors: Okazaki, Tomohisa, Hirahara, Kazuro, Ito, Takeo, Kano, Masayuki, Ueda, Naonori
• Format: Journal Article
• Language: English
• Published: Wiley 01.03.2025

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 inverse probl...