M. B. Dehkordi

Learning reduced-order latent linear models for Kalman filtering of nonlinear systems

A filtering-oriented end-to-end learning framework to identify reduced-order models explicitly tailored for state estimation in high-dimensional nonlinear systems and quantifies probabilistic bounds on the performance gap between full-order and reduced-order filters using conformal predictions, which do not require ass...