Publications by Professor Chris Oates - ePrints

Browsing publications by Professor Chris Oates.

Newcastle Authors	Title	Year
Professor Chris Oates	Scalable Monte Carlo for Bayesian Learning	2025
Takuo Matsubara Professor Chris Oates	Generalized Bayesian Inference for Discrete Intractable Likelihood	2024
Professor Chris Oates	Online Semiparametric Regression via Sequential Monte Carlo	2024
Professor Chris Oates	Probabilistic Richardson Extrapolation	2024
Professor Emilio Porcu Professor Chris Oates	The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning	2024
Professor Chris Oates	Cell to Whole Organ Global Sensitivity Analysis on a Four-chamber Electromechanics Model Using Gaussian Processes Emulators	2023
Matthew Fisher Professor Chris Oates	Gradient-Free Kernel Stein Discrepancy	2023
Matthew Fisher Professor Chris Oates	Gradient-Free Kernel Stein Discrepancy	2023
Dr Toni Karvonen Professor Chris Oates	Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed	2023
Professor Chris Oates	Meta-learning Control Variates: Variance Reduction with Limited Data	2023
Professor Chris Oates	Regularized Zero-Variance Control Variates	2023
Professor Chris Oates	Review of "Probabilistic Numerics" by Hennig, Osborne and Kersting	2023
Professor Emilio Porcu Professor Chris Oates	Sobolev Spaces, Kernels and Discrepancies over Hyperspheres	2023
Professor Chris Oates	Statistical properties of BayesCG under the Krylov prior	2023
Professor Chris Oates	Statistical properties of BayesCG under the Krylov prior	2023
Congye Wang Dr Heishiro Kanagawa Professor Chris Oates	Stein Π-Importance Sampling	2023
Professor Chris Oates	Stein’s Method Meets Computational Statistics: A Review of Some Recent Developments	2023
Professor Chris Oates Professor Emilio Porcu	A Riemann–Stein kernel method	2022
Professor Chris Oates Dr Liam Fleming	A Statistical Approach to Surface Metrology for 3D-Printed Stainless Steel	2022
Professor Chris Oates	Minimum Kernel Discrepancy Estimators	2022
Professor Chris Oates	Optimal thinning of MCMC output	2022
Professor Chris Oates	Parameter Space Reduction for Four-chamber Electromechanics Simulations Using Gaussian Processes Emulators	2022
Professor Chris Oates	Postprocessing of MCMC	2022
Takuo Matsubara Professor Chris Oates	Robust generalised Bayesian inference for intractable likelihoods	2022
Professor Chris Oates	Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization	2022
Professor Chris Oates	Semi-Exact Control Functionals From Sard's Method	2022
Dr Matt Graham Professor Chris Oates	Testing Whether a Learning Procedure is Calibrated	2022
Dr Liam Fleming Professor Peter Gosling Professor Chris Oates	A Data-Centric Approach to Generative Modelling for 3D-Printed Steel	2021
Dr Junyang Wang Professor Chris Oates	Bayesian numerical methods for nonlinear partial differential equations	2021
Dr Onur Teymur Professor Chris Oates	Black Box Probabilistic Numerics	2021
Professor Chris Oates Professor Kevin Wilson	Causal Graphical Models for Systems-Level Engineering Assessment	2021
Professor Chris Oates	Improved Calibration of Numerical Integration Error in Sigma-Point Filters	2021
Professor Chris Oates	Integration In Reproducing Kernel Hilbert Spaces Of Gaussian Kernels	2021
Matthew Fisher Dr Matt Graham Dr Dennis Prangle Professor Chris Oates	Measure Transport with Kernel Stein Discrepancy	2021
Matthew Fisher Dr Matt Graham Dr Dennis Prangle Professor Chris Oates	Measure Transport with Kernel Stein Discrepancy	2021
Dr Onur Teymur Professor Chris Oates	Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy	2021
Dr Onur Teymur Professor Chris Oates	Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy	2021
Professor Chris Oates	Probabilistic Iterative Methods for Linear Systems	2021
Takuo Matsubara Professor Chris Oates	The ridgelet prior: A covariance function approach to prior specification for Bayesian neural networks	2021
Matthew Fisher Professor Chris Oates	A Locally Adaptive Bayesian Cubature Method	2020
Professor Chris Oates	A Role for Symmetry in the Bayesian Solution of Differential Equations	2020
Professor Chris Oates	Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions	2020
Professor Chris Oates Dr Dennis Prangle	Optimality Criteria for Probabilistic Numerical Methods	2020
Professor Chris Oates	A Bayesian Conjugate Gradient Method	2019
Professor Chris Oates	A modern retrospective on probabilistic numerics	2019
Professor Chris Oates	Bayesian Probabilistic Numerical Methods	2019
Professor Chris Oates	Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment	2019
Professor Chris Oates	Causal learning via manifold regularization	2019
Professor Chris Oates	Convergence rates for a class of estimators based on Stein’s method	2019
Professor Chris Oates	Editorial: special edition on probabilistic numerics	2019
Professor Chris Oates	Optimal Monte Carlo integration on closed manifolds	2019
Professor Chris Oates	Probabilistic Integration: A Role in Statistical Computation?	2019
Professor Chris Oates	Rejoinder: Probabilistic Integration: A Role in Statistical Computation?	2019
Professor Chris Oates	Stein Point Markov Chain Monte Carlo	2019
Professor Chris Oates	Symmetry Exploits for Bayesian Cubature Methods	2019
Professor Chris Oates	A Bayes-Sard Cubature Method	2018
Professor Chris Oates	Graphical Models in Molecular Systems Biology	2018
Professor Chris Oates	On the Bayesian Solution of Differential Equations	2018
Professor Chris Oates	Stein Points	2018
Professor Chris Oates	Control functionals for Monte Carlo integration	2017
Professor Chris Oates	Investigation of the Widely Applicable Bayesian Information Criteria	2017
Professor Chris Oates	On the Sampling Problem for Kernel Quadrature	2017
Professor Chris Oates	Probabilistic Models for Integration Error in Assessment of Functional Cardiac Models	2017
Professor Chris Oates	Repair of Partly Misspecified Causal Diagrams	2017
Professor Chris Oates	Control Functionals for Quasi-Monte Carlo Integration	2016
Professor Chris Oates	Estimating Causal Structure Using Conditional DAG Models	2016
Professor Chris Oates	Exact Estimation of Multiple Directed Acyclic Graphs	2016
Professor Chris Oates	Exploiting Multi-Core Architectures for Reduced-Variance Estimation with Intractable Likelihoods	2016
Professor Chris Oates	Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems	2016
Professor Chris Oates	RNA editing generates sequence diversity within cell populations	2016
Professor Chris Oates	The Controlled Thermodynamic Integral for Bayesian Model Evidence Evaluation	2016
Professor Chris Oates	Accelerated Non-parametrics for Cascades of Poisson Processes	2015
Professor Chris Oates	Decoupling of the PI3K pathway via mutation necessitates combinatorial treatment in HER2+ breast cancer	2015
Professor Chris Oates	Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees	2015
Professor Chris Oates	Towards a Multisubject Analysis of Neural Connectivity	2015
Professor Chris Oates	A stochastic model dissects cell states in biological transition processes	2014
Professor Chris Oates	Causal network inference using biochemical kinetics	2014
Professor Chris Oates	Joint Estimation of Multiple Related Biological Networks	2014
Professor Chris Oates Sunil Mukherjee	Joint Structure Learning of Multiple Non-Exchangeable Networks	2014
Professor Chris Oates	Quantifying the Multi-Scale Performance of Network Inference Algorithms	2014
Professor Chris Oates	Single-Cell States in the Estrogen Response of Breast Cancer Cell Lines	2014