most citedBayesian seismic tomography based on velocity-space Stein variational gradient descent for physics-informed neural network

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physics.geo-ph2024

Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination

Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie

Subsurface seismic velocity structure is essential for earthquake source studies, including hypocenter determination. Conventional hypocenter determination methods ignore the inher…

physics.geo-ph2023★ 1 cited

Bayesian seismic tomography based on velocity-space Stein variational gradient descent for physics-informed neural network

Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie

In this study, we propose a Bayesian seismic tomography inference method using physics-informed neural networks (PINN). PINN represents a recent advance in deep learning, offering…