Presents fpBPINN framework using FPI-BPINN and fParVI-PINN to enable functional priors in Bayesian PINN-based PDE inversion, with random Fourier features aiding Gaussian prior representation.
46 Zhao et al., 2026 Lindseth, R
2 Pith papers cite this work. Polarity classification is still indexing.
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physics.geo-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Different parametrizations of the same geophysical inverse problem yield inconsistent Bayesian posterior distributions and deterministic inversion results even when they encode identical information.
citing papers explorer
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Functional-prior-based Bayesian PDE-constrained inversion using PINNs
Presents fpBPINN framework using FPI-BPINN and fParVI-PINN to enable functional priors in Bayesian PINN-based PDE inversion, with random Fourier features aiding Gaussian prior representation.
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Designing Solutions to Geophysical Inverse Problems by Changing Variables
Different parametrizations of the same geophysical inverse problem yield inconsistent Bayesian posterior distributions and deterministic inversion results even when they encode identical information.