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Hierarchical Bayesian Inversion of Global Variables and Large‐Scale Spatial Fields
Water Resources Research, 2022Lijing Wang +2 more
exaly
2022
We consider linear, mildly ill-posed inverse problems in separable Hilbert spaces under Gaussian noise, whose covariance operator is not identity (i.e. it is not a white noise problem), and use the Bayesian approach to nd their regularised solution. Speci cally, our goal is to regularise the prior in such a way that the posterior distribution achieves ...
openaire +2 more sources
We consider linear, mildly ill-posed inverse problems in separable Hilbert spaces under Gaussian noise, whose covariance operator is not identity (i.e. it is not a white noise problem), and use the Bayesian approach to nd their regularised solution. Speci cally, our goal is to regularise the prior in such a way that the posterior distribution achieves ...
openaire +2 more sources
Bayesian model inversion using stochastic spectral embedding
Journal of Computational Physics, 2021Paul-Remo Wagner +2 more
exaly
2011
The posterior distribution in a nonparametric inverse problem is shown to contract to the true parameter at a rate that depends on the smoothness of the parameter, and the smoothness and scale of the prior. Correct combinations of these characteristics lead to the minimax rate.
Knapik, B.T. +2 more
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The posterior distribution in a nonparametric inverse problem is shown to contract to the true parameter at a rate that depends on the smoothness of the parameter, and the smoothness and scale of the prior. Correct combinations of these characteristics lead to the minimax rate.
Knapik, B.T. +2 more
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A novel trans-dimensional Bayesian inversion strategy for airborne time-domain electromagnetic data
Journal of Applied Geophysics, 2022Xiaodong Yu
exaly
Bayesian Inversion with TimeOptMCMC
TimeOptMCMC (Meyers and Malinverno, 2018) is a Bayesian approach for evaluating cyclostratigraphic records that quantitatively links geologic data with astronomical theory. This manuscript provides an introductory guide for conducting a TimeOptMCMC Bayesian inversion, following the approach of Meyers and Malinverno (2018).openaire +1 more source
Accelerated Bayesian Inversion of Transient Electromagnetic Data Using MCMC Subposteriors
IEEE Transactions on Geoscience and Remote Sensing, 2021Hai Li, Guoqiang Xue, Linbo Zhang
exaly
An Improved Bayesian von Karman Regularization Method for the Joint Inversion of GNSS and InSAR Data
Journal of Surveying Engineering, - ASCE, 2023Leyang Wang, Wang Leyang, Xu Guangyu
exaly