This workshop was held at the Alan Turing Institute, London, England.
The accuracy and robustness of numerical predictions that are based on mathematical models depend critically upon the construction of accurate discrete approximations to key quantities of interest. The exact error due to approximation will be unknown to the analyst, but worst-case upper bounds can often be obtained. This working group worked toward developing Probabilistic Numerical Methods, which provide the analyst with a richer, probabilistic quantification of the numerical error in their output, thus providing better tools for reliable statistical inference.
The workshop included the presentation and critical discussion of WG research results, strategic planning of future activities and addressing grand challenges.
Additional Program Information and Supporting Media
- To see the schedule and abstracts from the lectures, please click HERE
- View the video below on the Summary Discussion: “A Euston Road Manifesto?”
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