An operator-split Bayesian posterior, which pushes independent neural-network posteriors for the source and boundary through the elliptic solution map, contracts around the true solution at a near-minimax rate.
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Operator-Split Bayesian Learning for Elliptic PDEs with Unequal Interior and Boundary Data
An operator-split Bayesian posterior, which pushes independent neural-network posteriors for the source and boundary through the elliptic solution map, contracts around the true solution at a near-minimax rate.