Multivariate Algorithms and their Foundations in Number Theory
Linz, October 15-December 21, 2018
High dimensional computation is a new frontier in scientific computing, with applications ranging from financial mathematics such as option pricing or risk management, to parameter estimation, to groundwater flow, heat transport, and wave propagation. Often the difficulties come from uncertainty or randomness in the data, and they present major challenges in the areas of Data Science and Uncertainty Quantification. This workshop provides a forum for interaction between international experts, with the aim to establish new collaborations.
In addition to the invited speakers, we will also have a small number of contributed talks.
On the Friday before the workshop, December 14, we will have 3 tutorials as an introduction on computational methods for PDEs with random coefficients. These tutorials will be given by Anthony Nouy (Ecole Centrale Nantes), Dirk Nuyens (KU Leuven) and Rob Scheichl (Heidelberg University). Everybody is welcome to attend.
"Uncertainty Quantification - Efficient Methods for PDEs with Random Coefficients"
Friday, Dec. 14, RICAM, Room SP2 416-2.
We have travel and accommodation support available for 8 PhD students at EUR600 each. Please encourage suitable candidates to apply. They need to send a 1 page resume + 3 paragraphs of motivation + a support letter from the supervisor to email@example.com before September 15. PhD students receiving travel and accommodation support must participate in the Friday tutorials.