Γ -convergence of Onsager–Machlup functionals: I. With applications to maximum a posteriori estimation in Bayesian inverse problems

DOI10.1088/1361-6420/ac3f81OpenAlexW4205937158MaRDI QIDQ5019928

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Publication date: 11 January 2022

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2108.04597

zbMATH Keywords

\(\Gamma\)-convergenceBayesian inverse problemstransition path theorysmall ball probabilitiesOnsager-Machlup functionalmaximum \textit{a posteriori} estimation

Mathematics Subject Classification ID

Parametric inference (62Fxx) Probabilistic methods, stochastic differential equations (65Cxx) Numerical analysis in abstract spaces (65Jxx)

Related Items (8)

Most probable transition paths in piecewise-smooth stochastic differential equations ⋮ Are Minimizers of the Onsager–Machlup Functional Strong Posterior Modes? ⋮ Strong maximum a posteriori estimation in Banach spaces with Gaussian priors ⋮ Maximum a posteriori estimators in ℓp are well-defined for diagonal Gaussian priors ⋮ The most probable transition paths of stochastic dynamical systems: a sufficient and necessary characterisation ⋮ On unifying randomized methods for inverse problems ⋮ An Order-Theoretic Perspective on Modes and Maximum A Posteriori Estimation in Bayesian Inverse Problems ⋮ Γ-convergence of Onsager–Machlup functionals: II. Infinite product measures on Banach spaces

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