On the lifting of deterministic convergence rates for inverse problems with stochastic noise
DOI10.3934/ipi.2017031zbMath1368.60073arXiv1604.07189OpenAlexW2963261054MaRDI QIDQ2360781
Ronny Ramlau, Andreas Hofinger, Daniel Gerth
Publication date: 12 July 2017
Published in: Inverse Problems and Imaging (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1604.07189
convergence ratesTikhonov regularizationill-posed problemBayesian approachstochastic inverse problem
Nonlinear ill-posed problems (47J06) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical methods for inverse problems for integral equations (65R32)
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