5 citations · 12 across the 15 of their papers we have counts for
3 papers · 1 filter
Propagating Model Uncertainty through Filtering-based Probabilistic Numerical ODE Solvers
Dingling Yao, Filip Tronarp, Nathanael Bosch
Filtering-based probabilistic numerical solvers for ordinary differential equations (ODEs), also known as ODE filters, have been established as efficient methods for quantifying nu…
Probabilistic ODE Solutions in Millions of Dimensions
Nicholas Krämer, Nathanael Bosch, Jonathan Schmidt +1
Probabilistic solvers for ordinary differential equations (ODEs) have emerged as an efficient framework for uncertainty quantification and inference on dynamical systems. In this w…
Pick-and-Mix Information Operators for Probabilistic ODE Solvers
Nathanael Bosch, Filip Tronarp, Philipp Hennig
Probabilistic numerical solvers for ordinary differential equations compute posterior distributions over the solution of an initial value problem via Bayesian inference. In this pa…