Jon Cockayne


PhD Student at University of Warwick

Papers


A Bayesian Conjugate Gradient Method
Jon Cockayne, Chris Oates, Ilse Ipsen, Mark Girolami
Bayesian Analysis, 2019, to appear with rejoinder
arXiv
Bayesian Probabilistic Numerical Methods
Jon Cockayne, Chris Oates, Tim Sullivan, Mark Girolami
SIAM Review, 2019, to appear
arXiv
Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment
Chris Oates, Jon Cockayne, Robert Aykroyd, Mark Girolami
Journal of the American Statistical Association, 2019
arXiv
Probabilistic Linear Solvers: A Unifying View
Simon Bartels, Jon Cockayne, Ilse Ipsen, Philipp Hennig
Statistics and Computing, 2019, to appear
arXiv
Convergence Rates for a Class of Estimators Based on Stein's Method
Chris Oates, Jon Cockayne, Francois-Xavier Briol, Mark Girolami
Bernoulli, 2019
arXiv
On the Bayesian Solution of Differential Equations
Junyang Wang, Jon Cockayne, Chris Oates
Proceedings of the 38th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 2017
arXiv
Probabilistic Numerical Methods for PDE-Constrained Bayesian Inverse Problems
Jon Cockayne, Chris Oates, Tim Sullivan, Mark Girolami
Proceedings of the 38th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 2016
arXiv

Talks


James H. Wilkinson Workshop, Manchester University
29-30 May 2019
Potsdam University
21 June 2019
SciCADE 2019
22-26 July 2019

Software


Please visit my github to find all of the software that I have made available from my research.

Libraries

bayesian_pdes
Implementation of the PDE solver from "Probabilistic Meshless Methods".
BCG
An implementation of the BayesCG algorithm from "A Bayesian Conjugate Gradient Method".
mcmc
Implementations of various MCMC routines in pure Python.
cmcmc
Implementations of various MCMC routines in C++.

Code from Papers

hydrocyclone_code
Code for reproducing results from "Bayesian PNM for Industrial Hydrocyclone Equipment".