Parametric Bayesian level set approach with radial basis expansion and Metropolis-Hastings sampling reconstructs acoustic sources from multiple frequency data, proving posterior well-posedness and showing competitive numerical results.
Santosa, A level-set approach for inverse problems involv- ing obstacles, ESAIM: Control, Optimization and Calculus of Variations, 1: 17-33
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A parametric Bayesian level set approach for acoustic source identification using multiple frequency information
Parametric Bayesian level set approach with radial basis expansion and Metropolis-Hastings sampling reconstructs acoustic sources from multiple frequency data, proving posterior well-posedness and showing competitive numerical results.