Applying Knothe-Rosenblatt transport maps to normalize the sparse Bayesian learning prior to a standard normal improves MCMC mixing on several non-log-concave inverse problems.
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Efficient sampling for sparse Bayesian learning using hierarchical prior normalization
Applying Knothe-Rosenblatt transport maps to normalize the sparse Bayesian learning prior to a standard normal improves MCMC mixing on several non-log-concave inverse problems.