24 citations · 54 across the 17 of their papers we have counts for
5 papers · 1 filter
Calibrated Adaptive Probabilistic ODE Solvers
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Probabilistic solvers for ordinary differential equations assign a posterior measure to the solution of an initial value problem. The joint covariance of this distribution provides…
Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes
Rui Gao, Filip Tronarp, Simo Särkkä
In this paper, we propose a class of efficient, accurate, and general methods for solving state-estimation problems with equality and inequality constraints. The methods are based…
Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space
Filip Tronarp, Simo Särkkä
In this paper the issue of filtering and smoothing in continuous discrete time is studied when the state variable evolves in some submanifold of Euclidean space, which may not have…
Bayesian ODE Solvers: The Maximum A Posteriori Estimate
Filip Tronarp, Simo Sarkka, Philipp Hennig
It has recently been established that the numerical solution of ordinary differential equations can be posed as a nonlinear Bayesian inference problem, which can be approximately s…
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions
Toni Karvonen, George Wynne, Filip Tronarp +2
Despite the ubiquity of the Gaussian process regression model, few theoretical results are available that account for the fact that parameters of the covariance kernel typically ne…