Workshop on Probabilistic Numerical Methods - Panel Discussion

Participate in a panel discussion exploring probabilistic numerical methods, part of the SAMSI Programme on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics. Delve into topics such as reference priors for probabilistic solutions of differential equations, heavy-tailed stable distributions for robust uncertainty quantification, statistical estimation with multi-resolution operator decompositions, and probabilistic numerical methods as Bayesian inversion methods. Gain insights from experts in the field as they discuss the development of these methods, which provide analysts with richer, probabilistic quantification of numerical errors in their outputs, enhancing tools for reliable statistical inference. Learn about the critical role of accurate discrete approximations in mathematical modeling and how probabilistic approaches can improve the accuracy and robustness of numerical predictions. For more information on this collaborative effort between the Alan Turing Institute, SAMSI, and Lloyd's Register Foundation, visit Prob-Num.org.

Introductions
Yousef Mizuki
Tim Sullivan
Question
Discussion