3 citations · 7 across the 9 of their papers we have counts for
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Black Box Probabilistic Numerics
Onur Teymur, Christopher N. Foley, Philip G. Breen +2
Probabilistic numerics casts numerical tasks, such the numerical solution of differential equations, as inference problems to be solved. One approach is to model the unknown quanti…
Bayesian Numerical Methods for Nonlinear Partial Differential Equations
Junyang Wang, Jon Cockayne, Oksana Chkrebtii +2
The numerical solution of differential equations can be formulated as an inference problem to which formal statistical approaches can be applied. However, nonlinear partial differe…
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…