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math.NA2025★ 1 cited
Uncertainty Quantification for Linear Inverse Problems with Besov Prior: A Randomize-Then-Optimize Method
Andreas Horst, Babak Maboudi Afkham, Yiqiu Dong +1
In this work, we investigate the use of Besov priors in the context of Bayesian inverse problems. The solution to Bayesian inverse problems is the posterior distribution which natu…
stat.CO2025★ 1 cited
Bayesian decomposition using Besov priors
Andreas Horst, Babak Maboudi Afkham, Yiqiu Dong +1
In many inverse problems, the unknown is composed of multiple components with different regularities, for example, in imaging problems, where the unknown can have both rough and sm…