3 papers
math.ST2026
Random tree Besov priors: Data-driven regularisation parameter selection
Hanne Kekkonen, Andreas Tataris
We develop a data-driven algorithm for automatically selecting the regularisation parameter in Bayesian inversion under random tree Besov priors. One of the key challenges in Bayes…
math.AP2025
A variational Lippmann-Schwinger-type approach for the Helmholtz impedance problem on bounded domains
Andreas Tataris, Alexander V. Mamonov
Recently, reduced order modeling methods have been applied to solving inverse boundary value problems arising in frequency domain scattering theory. A key step in projection-based…
math.NA2025
Inverse scattering for Schrödinger equation in the frequency domain via data-driven reduced order modeling
Andreas Tataris, Tristan van Leeuwen, Alexander V. Mamonov
In this paper we develop a numerical method for solving an inverse scattering problem of estimating the scattering potential in a Schrödinger equation from frequency domain measur…