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Seminar on Control Theory and Nonlinear Filtering
Extension of probability flow on matrix Lie group
Extension of probability flow on matrix Lie group
Organizer
Speaker
Time
Tuesday, January 17, 2023 9:30 PM - 10:00 PM
Venue
Online
Abstract
Feedback control for the probability flow is firstly proposed by Prashant G. Mehta et al. Given a smooth path ${p_t^*in mathcal{P}_2(mathbb{R}^d)}$, basic problem is to design stochastic process ${{X}_t}$ such that the probability density ${p}_t$ equals to $p_t^*$ for any time $tge 0$. Note that it acts as a general framework. Solution of probability flow is of interests in many applied areas. Up to 2021, there exist complete formulation under Euclidean space. In this talk, we will discuss the extension to matrix Lie group. We will discuss two cases: deterministic and stochastic probability flow.
Speaker Intro
Jiao Xiaopei graduated with a bachelor's degree from the Zhi Yuan College of Shanghai Jiao Tong University (Physics Department) in 2017 and obtained his PhD from the Department of Mathematical Sciences at Tsinghua University in 2022, under the guidance of Professor Stephen Shing-Toung Yau (IEEE Fellow, former tenured professor at the University of Illinois at Chicago). He has conducted postdoctoral research at the Beijing Institute of Mathematica Science and Application and at the University of Twente in the Netherlands (under the guidance of Professor Johannes Schmidt-Hieber, Fellow of the Institute of Mathematical Statistics). His current research interests include control theory, numerical partial differential equations, and bioinformatics.