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Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion
However, selecting appropriate prior information in a probabilistic inversion is crucial, yet non-trivial, as it influences the ability of a sampling-based inference in providing geological realism in the posterior samples.
Laplace HypoPINN: Physics-Informed Neural Network for hypocenter localization and its predictive uncertainty
This work focuses on predicting the hypocenter locations using HypoPINN and investigates the propagation of uncertainties from the random realizations of HypoPINN's weights and biases using the Laplace approximation.
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