3 papers
stat.ML2025
Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems
Robert Gruhlke, Matei Hanu, Claudia Schillings +1
We introduce a gradient-free framework for Bayesian Optimal Experimental Design (BOED) in sequential settings, aimed at complex systems where gradient information is unavailable. O…
math.NA2023
On the ensemble Kalman inversion under inequality constraints
Matei Hanu, Simon Weissmann
The ensemble Kalman inversion (EKI), a recently introduced optimisation method for solving inverse problems, is widely employed for the efficient and derivative-free estimation of…
math.NA2023
Ensemble Kalman Inversion for Image Guided Guide Wire Navigation in Vascular Systems
Matei Hanu, Jürgen Hesser, Guido Kanschat +3
This paper addresses the challenging task of guide wire navigation in cardiovascular interventions, focusing on the parameter estimation of a guide wire system using Ensemble Kalma…