Oracle-type posterior contraction rates in Bayesian inverse problems
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Publication:256079
DOI10.3934/ipi.2015.9.895zbMath1332.62098OpenAlexW2556635976MaRDI QIDQ256079
Shuai Lu, Peter Mathé, Kui Lin
Publication date: 9 March 2016
Published in: Inverse Problems and Imaging (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/ipi.2015.9.895
Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Numerical solution to inverse problems in abstract spaces (65J22)
Related Items (13)
Posterior Contraction in Bayesian Inverse Problems Under Gaussian Priors ⋮ Multi-task learning via linear functional strategy ⋮ Tikhonov regularization with oversmoothing penalty for nonlinear statistical inverse problems ⋮ Convergence analysis of Tikhonov regularization for non-linear statistical inverse problems ⋮ Inverse learning in Hilbert scales ⋮ Randomized matrix approximation to enhance regularized projection schemes in inverse problems ⋮ Kernel regression, minimax rates and effective dimensionality: Beyond the regular case ⋮ On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise ⋮ Weak-norm posterior contraction rate of the 4DVAR method for linear severely ill-posed problems ⋮ Importance sampling: intrinsic dimension and computational cost ⋮ Balancing principle in supervised learning for a general regularization scheme ⋮ Bayesian inverse problems with non-commuting operators ⋮ Adaptive discretization for signal detection in statistical inverse problems
Uses Software
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