Year: 2025
Type: conference-paper
Abstract: We investigate the use of normalizing flows to approximate transport maps from tractable reference densities to complex Bayesian posterior distributions for Bayesian model updating.A Gaussian process (GP) surrogate with active sampling is used to provide a differentiable target density for optimizing the transport map.While results show normalizing flows can capture multimodal behavior in a simple example, further work is needed to refine the active sampling strategy and enable mode identification in the GP surrogate for robust multimodal density approximation.
Authors: F. Mett, J. Grashorn, T. Potthast, M. Broggi, M. Beer
Institutions: Leibniz University Hannover, Helmut Schmidt University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4411488947