10 citations · 12 across the 5 of their papers we have counts for
5 papers
Score-based diffusion models for severely ill-posed problems in diffuse optical tomography
Fabian Schneider, Meghdoot Mozumder, Konstantin Tamarov +4
Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems, enabling high-quality reconstructions in inverse problems by le…
An Unconditional Representation of the Conditional Score in Infinite-Dimensional Linear Inverse Problems
Fabian Schneider, Duc-Lam Duong, Matti Lassas +2
Score-based diffusion models (SDMs) have emerged as a powerful tool for sampling from the posterior distribution in Bayesian inverse problems. However, existing methods often requi…
Stability of particle trajectories of scalar conservation laws and applications in Bayesian inverse problems
Masoumeh Dashti, Duc-Lam Duong
We consider the scalar conservation law in one space dimension with a genuinely nonlinear flux. We assume that an appropriate velocity function depending on the entropy solution of…
Stability estimates for the expected utility in Bayesian optimal experimental design
Duc-Lam Duong, Tapio Helin, Jose Rodrigo Rojo-Garcia
We study stability properties of the expected utility function in Bayesian optimal experimental design. We provide a framework for this problem in a non-parametric setting and prov…
Reformulating the SIR model in terms of the number of COVID-19 detected cases: well-posedness of the observational model
Eduard Campillo-Funollet, Hayley Wragg, James Van Yperen +2
Compartmental models are popular in the mathematics of epidemiology for their simplicity and wide range of applications. Although they are typically solved as initial value problem…