works on
bayesian inverse problems 1discrete-to-continuum limits 1gaussian fluctuations 1map estimation 1posterior convergence 1

From the 1 of 4 linked papers with an AI index.

collaborators

4 papers

math.ST2026

Discrete to continuum limits in Bayesian inverse problems

Alexander Katsevich

The paper establishes how discrete Bayesian inverse problems with finite-difference priors converge to well-defined continuum priors and posteriors, and shows that the discrete MAP…

math.CA2026

High-dimensional Laplace asymptotics up to the concentration threshold

Alexander Katsevich, Anya Katsevich

We study high-dimensional Laplace-type integrals in the regime where both and are large. Existing rigorous Lapl…

math.NA2025

Local Characterization of Noise in Iterative Reconstruction of the Generalized Radon Transform

Alexander Katsevich

We study noise in iterative reconstruction from discrete noisy data of a generalized Radon transform in the plane. Our approach builds on Local Reconstruction Analysis (LRA), a fra…

math.NA2025

Local analysis of iterative reconstruction from discrete generalized Radon transform data in the plane

Alexander Katsevich

Local reconstruction analysis (LRA) is a powerful and flexible technique to study images reconstructed from discrete generalized Radon transform (GRT) data, . The m…