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We study Cauchy-distributed difference priors for edge-preserving Bayesian statistical inverse problems.
Stable non-Gaussian Random Processes
Samorodnitsky G and Taqqu M S 1994 · 1994
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Markov Chain Monte Carlo in Practice
Gilks W R, Richardson S and Spiegelhalter D J 1996 · 1996
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Bayesian Data Analysis, 2nd edn
Gelman A, Carlin J B, Stern H S and Rubin D B 2003 · 2003
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Can one use total variation prior for edge preserving Bayesian inversion?
Lassas M and Siltanen S 2004 · 2004
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Lasanen S and Roininen L 2005 Statistical inversion with Green’s priors 5th Int. Conf. Inv. Prob. Eng. Proc
2005
Earlier work this paper cites.
Discretization-invariant Bayesian inversion and Besov space priors
Lassas M, Saksman E and Siltanen S 2009 · 2009
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Vänskä S, Lassas M and Siltanen S 2009 Statistical X-ray tomography using empirical Besov priors Int. J. Tomog. Stat
2009
Cited alongside, same era.
Lindgren F, Rue H and Lindström J 2011 An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach Journal of the Royal Statistical Society: Series B
2011
Cited alongside, same era.
Roininen L, Lehtinen M, Lasanen S, Orispää M and Markkanen M 2011 Correlation priors Inverse Problems and Imaging
2011
Cited alongside, same era.
Non-Gaussian statistical inverse problems. Part I: Posterior distributions
Lasanen S 2012 · 2012
Cited alongside, same era.
Non-Gaussian statistical inverse problems. Part II: Posterior convergence for approximated unknowns
Lasanen S 2012 · 2012
Later among the works it cites.
Roininen L, Piiroinen P and Lehtinen M 2013 Constructing continuous stationary covariances as limits of the second-order stochastic difference equations Inverse Problems and Imaging
2013
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Roininen L, Huttunen J and Lasanen S 2014 Whittle-Matérn priors for Bayesian statistical inversion with applications to electrical impedance tomography Inverse Problems and Imaging
2014
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2016
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