Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks

Ryoichiro Agata, Tomohisa Okazaki

Physics-informed neural networks (PINNs) provide a mesh-free framework for solving PDE-constrained inverse problems, but their extension to Bayesian inversion still faces a fundame…