On solving Ordinary Differential Equations using Gaussian Processes
Methodology
2014-08-19 v1 Numerical Analysis
Numerical Analysis
Computation
Machine Learning
Abstract
We describe a set of Gaussian Process based approaches that can be used to solve non-linear Ordinary Differential Equations. We suggest an explicit probabilistic solver and two implicit methods, one analogous to Picard iteration and the other to gradient matching. All methods have greater accuracy than previously suggested Gaussian Process approaches. We also suggest a general approach that can yield error estimates from any standard ODE solver.
Keywords
Cite
@article{arxiv.1408.3807,
title = {On solving Ordinary Differential Equations using Gaussian Processes},
author = {David Barber},
journal= {arXiv preprint arXiv:1408.3807},
year = {2014}
}