学术报告:10月25号10:00-11:00,西安交通大学--贾骏雄

发布者:吕小俊发布时间:2019-10-24浏览次数:755

东南大学数学学院邀请专家申请表

  

报告人

贾骏雄

单位

西安交通大学

报告题目

Variational Bayes' method for   functions and its applications to inverse problems

报告时间

1025日周五

1000-1100

地点

东南大学数学学院   第一报告厅

邀请人

闫 亮

报告摘要

Bayesian approach as a useful tool for   quantifying uncertainties has been widely used for solving inverse problems   of partial differential equations (IPPDE). One of the key difficulties for   employing Bayesian approach is how to extract information from the posterior   probability measure. Variational Bayes’ method (VBM) is one of the most   activate research topics in the field of machine learning, which has the   ability to extract posterior information approximately by using much lower   computational resources compared with the sampling type method. In this talk,   we generalize the usual finite-dimensional VBM to infinite-dimensional space,   which makes the usage of VBM for IPPDE rigorously. General   infinite-dimensional mean-field approximation theory has been established,   and has been applied to abstract linear inverse problems with Gaussian and   Laplace noise assumption. Finally, two numerical examples are given which   illustrate the effectiveness of the proposed approach. 

报告人简介

贾骏雄博士2015年毕业于西安交通大学且于同年留校任教,2017年聘为西安交通大学数学学院副教授,主要研究领域为反问题的贝叶斯推断方法。主持国家自然科学基金青年、面上项目各一项,2017年获得陕西省优秀博士学位论文奖、陕西省数学会优秀论文奖,2018年获西安交通大学第四届十大学术新人奖,2019年作为第二获奖人获得陕西省高等学校科学技术二等奖。在Inverse   Probl., J. Funct. Anal., Inverse Probl. Imag., J. Appl. Geophys., J.   Differential Equations等国际著名期刊上共发表论文25篇。