7 citations · 13 across the 3 of their papers we have counts for
3 papers
stat.ML2021★ 5 cited
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…
stat.ML2021★ 1 cited
Linear-Time Probabilistic Solutions of Boundary Value Problems
Nicholas Krämer, Philipp Hennig
We propose a fast algorithm for the probabilistic solution of boundary value problems (BVPs), which are ordinary differential equations subject to boundary conditions. In contrast…
stat.ML2020★ 7 cited
Stable Implementation of Probabilistic ODE Solvers
Nicholas Krämer, Philipp Hennig
Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their co…