Probabilistic integration

FX Briol, CJ Oates, M Girolami, MA Osborne… - Statistical Science, 2019 - JSTOR
A research frontier has emerged in scientific computation, wherein discretisation error is
regarded as a source of epistemic uncertainty that can be modelled. This raises several …

A big data analysis approach for rail failure risk assessment

A Jamshidi, S Faghih‐Roohi, S Hajizadeh… - Risk …, 2017 - Wiley Online Library
Railway infrastructure monitoring is a vital task to ensure rail transportation safety. A rail
failure could result in not only a considerable impact on train delays and maintenance costs …

A modern retrospective on probabilistic numerics

CJ Oates, TJ Sullivan - Statistics and computing, 2019 - Springer
This article attempts to place the emergence of probabilistic numerics as a mathematical–
statistical research field within its historical context and to explore how its gradual …

Bayesian online regression for adaptive direct illumination sampling

P Vévoda, I Kondapaneni, J Křivánek - ACM Transactions on Graphics …, 2018 - dl.acm.org
Direct illumination calculation is an important component of any physically-based Tenderer
with a substantial impact on the overall performance. We present a novel adaptive solution …

Conditional Bayesian Quadrature

Z Chen, M Naslidnyk, A Gretton, FX Briol - ar** (SLAM)
method based on multi-agent particle swarm optimized particle filter (MAPSOPF) was …

Sobolev spaces, kernels and discrepancies over hyperspheres

S Hubbert, E Porcu, C Oates, M Girolami - arxiv preprint arxiv …, 2022 - arxiv.org
This work provides theoretical foundations for kernel methods in the hyperspherical context.
Specifically, we characterise the native spaces (reproducing kernel Hilbert spaces) and the …

Symmetry exploits for Bayesian cubature methods

T Karvonen, S Särkkä, CJ Oates - Statistics and Computing, 2019 - Springer
Bayesian cubature provides a flexible framework for numerical integration, in which a priori
knowledge on the integrand can be encoded and exploited. This additional flexibility …

Gaussian process for radiance functions on the sphere

R Marques, C Bouville… - Computer Graphics …, 2022 - Wiley Online Library
Efficient approximation of incident radiance functions from a set of samples is still an open
problem in physically based rendering. Indeed, most of the computing power required to …