Posterior consistency and convergence rates for Bayesian inversion with hypoelliptic operators
From MaRDI portal
Publication:2820674
DOI10.1088/0266-5611/32/8/085005zbMath1390.35422arXiv1507.01772OpenAlexW1786480885MaRDI QIDQ2820674
Samuli Siltanen, Hanne Kekkonen, Matti Lassas
Publication date: 9 September 2016
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1507.01772
Related Items (14)
Designing truncated priors for direct and inverse Bayesian problems ⋮ A Bernstein–von-Mises theorem for the Calderón problem with piecewise constant conductivities ⋮ Consistency of Bayesian inference with Gaussian process priors for a parabolic inverse problem ⋮ Optimization based methods for partially observed chaotic systems ⋮ Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem ⋮ Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems ⋮ Importance sampling: intrinsic dimension and computational cost ⋮ Posterior contraction for empirical Bayesian approach to inverse problems under non-diagonal assumption ⋮ Bernstein--von Mises Theorems and Uncertainty Quantification for Linear Inverse Problems ⋮ Modern regularization methods for inverse problems ⋮ Solving inverse problems using data-driven models ⋮ Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors ⋮ Bernstein-von Mises theorems for statistical inverse problems. I: Schrödinger equation ⋮ Material-separating regularizer for multi-energy x-ray tomography
This page was built for publication: Posterior consistency and convergence rates for Bayesian inversion with hypoelliptic operators
