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math.NA2018★ 1 cited
Characterizing impacts of model uncertainties in quantitative photoacoustics
Kui Ren, Sarah Vallélian
This work is concerned with uncertainty quantification problems for image reconstructions in quantitative photoacoustic imaging (PAT), a recent hybrid imaging modality that utilize…
math.NA2018
Image reconstruction in quantitative photoacoustic tomography with the simplified approximation
Christina Frederick, Kui Ren, Sarah Vallélian
Photoacoustic tomography (PAT) is a hybrid imaging modality that intends to construct high-resolution images of optical properties of heterogeneous media from measured acoustic dat…
math.NA2016★ 2 cited
Low Rank Independence Samplers in Bayesian Inverse Problems
D. Andrew Brown, Arvind Saibaba, Sarah Vallélian
In Bayesian inverse problems, the posterior distribution is used to quantify uncertainty about the reconstructed solution. In practice, Markov chain Monte Carlo algorithms often ar…