3 papers
math.ST2026
Wasserstein bounds for non-linear Gaussian filters
Toni Karvonen, Simo Särkkä
Most Kalman filters for non-linear systems, such as the unscented Kalman filter, are based on Gaussian approximations. We use Poincaré inequalities to bound the Wasserstein distan…
math.ST2025
Scale estimation and rate-unbiasedness for Gaussian processes under smoothness misspecification
Toni Karvonen, François Bachoc
Gaussian process regression is used throughout statistics and machine learning for prediction and uncertainty quantification. A Gaussian process is specified by its mean and covari…
math.ST2025
Error analysis for a statistical finite element method
Toni Karvonen, Fehmi Cirak, Mark Girolami
The recently proposed statistical finite element (statFEM) approach synthesises measurement data with finite element models and allows for making predictions about the unknown true…