Newcastle University
Toggle Main Menu
Toggle Search
Home
Browse
Latest
Policies
About
Home
Browse
Latest
Policies
About
ePrints
Browse by author
Browsing publications by
Professor Chris Oates.
Newcastle Authors
Title
Year
Full text
Takuo Matsubara
Professor Chris Oates
Generalized Bayesian Inference for Discrete Intractable Likelihood
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