140 citations · 1.9k across the 86 of their papers we have counts for
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Theoretical Guarantees for the Statistical Finite Element Method
Yanni Papandreou, Jon Cockayne, Mark Girolami +1
The statistical finite element method (StatFEM) is an emerging probabilistic method that allows observations of a physical system to be synthesised with the numerical solution of a…
Digital twinning of self-sensing structures using the statistical finite element method
Eky Febrianto, Liam Butler, Mark Girolami +1
The monitoring of infrastructure assets using sensor networks is becoming increasingly prevalent. A digital twin in the form of a finite element model, as used in design and constr…
Integration in reproducing kernel Hilbert spaces of Gaussian kernels
Toni Karvonen, Chris J. Oates, Mark Girolami
The Gaussian kernel plays a central role in machine learning, uncertainty quantification and scattered data approximation, but has received relatively little attention from a numer…
Embedded Ridge Approximations
Chun Yui Wong, Pranay Seshadri, Geoffrey Parks +1
Many quantities of interest (qois) arising from differential-equation-centric models can be resolved into functions of scalar fields. Examples of such qois include the lift over an…
Probabilistic Numerics and Uncertainty in Computations
Philipp Hennig, Michael A Osborne, Mark Girolami
We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equation…