51 citations · 289 across the 43 of their papers we have counts for
3 papers · 2 filters
Statistical inverse learning and -regularization
Abhishake Rastogi, Tatiana A. Bubba, Tapio Helin +1
We study the recovery of sparse functions from finite, noisy, and indirect observations in the framework of statistical inverse learning. The unknown is modeled as an element of $\…
A Convex Approximation Framework for Neural Likelihood-Based Bayesian Inverse Problems
Fabian Schneider, Tapio Helin, Leila Taghizadeh
Many problems in science and engineering are difficult to model accurately, either due to unknown physical mechanisms, poorly quantified measurement uncertainty, or prohibitive com…
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…