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Efficient Stochastic Collocation Methods for Uncertainty Quantification
Date: 2015/9/8             Browse: 511

Speaker: Tao Zhou (Chinese Academy of Sciences)

Time: Sept. 10th, 9:30am – 10:30am

Location: Room 220, Building 8

Abstract:

The talk is concerned with the multivariate stochastic collocation methods on unstructured grids. The motivation for such a study is the applications in parametric Uncertainty Quantification (UQ). We shall first give a general framework of stochastic collocation methods, which include approaches such as compressed sensing, least-squares, and interpolation. Particular attention will be then given to the least-squares approach, and we will review recent progresses.

The talk is based on joint works with A. Narayan (Umass, USA), J. Jackman (Sandia, USA), Z. Xu (AMSS, CAS)

Bio:

报告人:周涛

中国科学院数学与系统科学研究院助理教授

最高学历: 博士研究生

最高学位: 理学博士

毕业院校: 中国科学院数学与系统科学研究院

研究方向: 随机计算方法,不确定性量化

主要成果: 随机守恒律方程数值方法,离散投影方法,稀疏插值


                                                       SIST-Seminar 15039