Search Results for author:
Found 4 papers, 1 papers with code
Black Box Probabilistic Numerics
One approach is to model the unknown quantity of interest as a random variable, and to constrain this variable using data generated during the course of a traditional numerical method.
Optimal quantisation of probability measures using maximum mean discrepancy
Several researchers have proposed minimisation of maximum mean discrepancy (MMD) as a method to quantise probability measures, i. e., to approximate a target distribution by a representative point set.
A Bayesian nonparametric test for conditional independence
This article introduces a Bayesian nonparametric method for quantifying the relative evidence in a dataset in favour of the dependence or independence of two variables conditional on a third.
Probabilistic Linear Multistep Methods
We present a derivation and theoretical investigation of the Adams-Bashforth and Adams-Moulton family of linear multistep methods for solving ordinary differential equations, starting from a Gaussian process (GP) framework.
