QMC Working Group II: Probabilistic Numerics

Group Leaders:

  • C. Oates (University of Newcastle Upon Tyne and Alan Turing Institute, UK)
  • T. J. Sullivan (Free University of Berlin, Germany)

Weekly Meetings: Meeting Times to be determined


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 aims, instead, to develop 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.

News and Updates:
Group Meeting
April 11-13, 2018

To get more information about this working group, visit their web page by clicking HERE

SAMSI Directorate Liaison: Ilse Ipsen

Questions: email qmc@samsi.info

Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics (QMC)