Research

Publications

Preprints

On the Bayesian Solution of Differential Equations
Junyang Wang; Jon Cockayne; Chris J. Oates
[arXiv]

A Bayesian Conjugate Gradient Method
Jon Cockayne; Chris J. Oates; Mark Girolami
[arXiv]

Bayesian Probabilistic Numerical Methods for Industrial Process Monitoring
Chris J. Oates; Jon Cockayne; Robert Ackroyd
[arXiv]

Bayesian Probabilistic Numerical Methods
Jon Cockayne; Chris J. Oates; Tim Sullivan; Mark Girolami
[arXiv]
Awarded “best student paper” by in the section on Bayesian Statistical Science, by the ASA

Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems
Jon Cockayne; Chris J. Oates; Tim Sullivan; Mark Girolami
[arXiv]

2018

Convergence Rates for a Class of Estimators Based on Stein’s Identity
Chris J. Oates; Jon Cockayne; F-X Briol; Mark Girolami
Bernoulli, To Appear
[arXiv]

2017

On the Sampling Problem for Kernel Quadrature
F-X Briol; Chris J. Oates; Jon Cockayne; Wilson J. Chen; Mark Girolami
International Conference on Machine Learning
[Journal] [arXiv]

Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems
Jon Cockayne; Chris Oates; Tim Sullivan; Mark Girolami
Proceedings of the 36th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
[Journal] [arXiv]

Contributed Discussion on Article by Chkrebtii, Campbell, Calderhead, and Girolami
Jon Cockayne as well as F-X Briol; Jon Cockayne; Onur Teymur
[Journal]


Selected Talks

When Where Title
6 Jun 2017 ICERM Workshop on Probabilistic Scientific Computation Bayesian Probabilistic Numerical Methods
1 Mar 2017 SIAM CSE Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems