5 papers · 1 filter
3D Uncertainty Quantification for the Photo-Acoustic Tomography
Babak Maboudi Afkham, Amal Mohammed A Alghami, Hassan Yazdanian +1
Photoacoustic tomography (PAT) is a promising modality for high-resolution biomedical imaging, motivating the need for reliable uncertainty quantification (UQ) of reconstructed ima…
Adjoint-Based Bayesian Uncertainty Quantification for PDE-Constrained Inverse Problems with Application to Semiconductor Imaging
Hassan Yazdanian, Leila Taghizadeh, Babak Maboudi Afkham
We formulate a Bayesian framework for reconstructing doping profiles in pn-junction semiconductor devices from boundary flux measurements. The unknown doping field is modeled as a…
QVaR: a Quantum Variational Regularization method for Linear Inverse Problems
Siiri Rautio, Hjørdis Schlüter, Andreas Hauptmann +1
We present a tailored framework for solving regularized linear inverse problems using quantum optimization methods. By discretizing the solution space and encoding data fidelity an…
Inhomogeneous Priors for Bayesian Inverse Problems
Babak Maboudi Afkham, Tomas Soto, Mirza Karamehmedovic +1
Many inverse problems arising in engineering and applied sciences involve unknown quantities with pronounced spatial inhomogeneity, such as localized defects or spatially varying m…
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…