Stochastic Computing and Uncertainty Quantification: Algorithms and Challenges
主 题: Stochastic Computing and Uncertainty Quantification: Algorithms and Challenges
报告人: Professor Dongbin Xiu (University of Utah)
时 间: 2015-10-23 15:00-16:00
地 点: 理科一号楼 1114(数学所活动）
The field of stochastic computation has received increasing amount of attention recently, driven by the need to conduct uncertainty quantification. Extensive research efforts have been devoted to it and many novel numerical techniques have been developed. These techniques aim to conduct efficient stochastic simulations for large-scale systems. Most notably, the algorithms based on the idea of generalized polynomial chaos (gPC), particularly the non-intrusive stochastic collocation methods, have found their use in many practical simulations. These methods utilize rigorous mathematical theory and deliver superior performance in practice. However, challenges exist, especially the curse-of-dimensionality. In this talk we will review these well known numerical algorithms, their strength and weakness. We will also review some of the most prominent challenges, such as the curse-of-dimensionality, and the solid, albeit limited, progresses that have been made.