Develops generalized Golub-Kahan based proposal distributions for efficient MCMC sampling in hierarchical Bayesian inverse problems with large parameter spaces and unknown hyperparameters.
Geoscientific Model Devel- opment 15(14), 5547–5565 (2022) 27
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Efficient sampling approaches based on generalized Golub-Kahan methods for large-scale hierarchical Bayesian inverse problems
Develops generalized Golub-Kahan based proposal distributions for efficient MCMC sampling in hierarchical Bayesian inverse problems with large parameter spaces and unknown hyperparameters.