26 citations · 58 across the 10 of their papers we have counts for
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stat.ME2018
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective
Filip Tronarp, Hans Kersting, Simo Särkkä +1
We formulate probabilistic numerical approximations to solutions of ordinary differential equations (ODEs) as problems in Gaussian process (GP) regression with non-linear measureme…
math.NA2018
Convergence Rates of Gaussian ODE Filters
Hans Kersting, T. J. Sullivan, Philipp Hennig
A recently-introduced class of probabilistic (uncertainty-aware) solvers for ordinary differential equations (ODEs) applies Gaussian (Kalman) filtering to initial value problems. T…