
Bayesian Numerical Methods for Nonlinear Partial Differential Equations
The numerical solution of differential equations can be formulated as an...
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Robust Generalised Bayesian Inference for Intractable Likelihoods
Generalised Bayesian inference updates prior beliefs using a loss functi...
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PostProcessing of MCMC
Markov chain Monte Carlo (MCMC) is the engine of modern Bayesian statist...
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Testing whether a Learning Procedure is Calibrated
A learning procedure takes as input a dataset and performs inference for...
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Probabilistic Iterative Methods for Linear Systems
This paper presents a probabilistic perspective on iterative methods for...
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Measure Transport with Kernel Stein Discrepancy
Measure transport underpins several recent algorithms for posterior appr...
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The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks
Bayesian neural networks attempt to combine the strong predictive perfor...
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Optimal quantisation of probability measures using maximum mean discrepancy
Several researchers have proposed minimisation of maximum mean discrepan...
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A Probabilistic Numerical Extension of the Conjugate Gradient Method
We present a Conjugate Gradient (CG) implementation of the probabilistic...
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Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
Control variates are a wellestablished tool to reduce the variance of M...
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Optimal Thinning of MCMC Output
The use of heuristics to assess the convergence and compress the output ...
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Integration in reproducing kernel Hilbert spaces of Gaussian kernels
The Gaussian kernel plays a central role in machine learning, uncertaint...
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SemiExact Control Functionals From Sard's Method
This paper focuses on the numerical computation of posterior expected qu...
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Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions
Despite the ubiquity of the Gaussian process regression model, few theor...
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Discussion of "Unbiased Markov chain Monte Carlo with couplings" by Pierre E. Jacob, John O'Leary and Yves F. Atchadé
This is a contribution for the discussion on "Unbiased Markov chain Mont...
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A Locally Adaptive Bayesian Cubature Method
Bayesian cubature (BC) is a popular inferential perspective on the cubat...
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A Role for Symmetry in the Bayesian Solution of Differential Equations
The interpretation of numerical methods, such as finite difference metho...
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Stein Point Markov Chain Monte Carlo
An important task in machine learning and statistics is the approximatio...
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Optimality Criteria for Probabilistic Numerical Methods
It is well understood that Bayesian decision theory and average case ana...
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Improved Calibration of Numerical Integration Error in SigmaPoint Filters
The sigmapoint filters, such as the UKF, which exploit numerical quadra...
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Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?"
This article is the rejoinder for the paper "Probabilistic Integration: ...
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Regularised ZeroVariance Control Variates for HighDimensional Variance Reduction
Zerovariance control variates (ZVCV) are a postprocessing method to r...
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A RiemannianStein Kernel Method
This paper presents a theoretical analysis of numerical integration base...
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Symmetry Exploits for Bayesian Cubature Methods
Bayesian cubature provides a flexible framework for numerical integratio...
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A BayesSard Cubature Method
This paper focusses on the formulation of numerical integration as an in...
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Stein Points
An important task in computational statistics and machine learning is to...
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Posterior Integration on a Riemannian Manifold
The geodesic Markov chain Monte Carlo method and its variants enable com...
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Posterior Integration on an Embedded Riemannian Manifold
This note extends the posterior integration method of Oates et al. (2016...
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On the Sampling Problem for Kernel Quadrature
The standard Kernel Quadrature method for numerical integration with ran...
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Probabilistic Integration: A Role in Statistical Computation?
A research frontier has emerged in scientific computation, wherein numer...
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FrankWolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
There is renewed interest in formulating integration as an inference pro...
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Exact Estimation of Multiple Directed Acyclic Graphs
This paper considers the problem of estimating the structure of multiple...
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Chris J. Oates
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