2 papers
math.NA2026
Dimension and model reduction approaches for linear Bayesian inverse problems with rank-deficient prior covariances
Josie König, Elizabeth Qian, Melina A. Freitag
Bayesian inverse problems use observed data to update a prior probability distribution for an unknown state or parameter of a scientific system to a posterior distribution conditio…
math.NA2025
Learning Stochastic Reduced Models from Data: A Nonintrusive Approach
M. A. Freitag, J. M. Nicolaus, M. Redmann
A nonintrusive model order reduction method for bilinear stochastic differential equations with additive noise is proposed. A reduced order model (ROM) is designed in order to appr…