报告题目：Data-driven computational methods for stochastic dynamics
报 告 人：李尧副 教授
所在单位：马萨诸塞大学
报告时间：2024年7月12 日 星期五 上午 10:00 - 11：00
报告地点： 数学楼第一报告厅
校内联系人：王式柔 shirou@jlu.edu.cn
报告摘要： In this talk, I will summarize our recent progress in using data-driven methods to numerically study the properties of stochastic differential equations. This includes (1) Solving both time-dependent Fokker-Planck equations and stationary Fokker-Planck equations, (2) Estimating the speed of convergence to the steady states, (3) Computing forward and backward eigenfunction of the Fokker-Planck equations, and (4) Solving the Freidlin-Wentzell quasi-potential function. Compared with traditional methods, our data-driven approaches are significantly more applicable to higher dimensional problems.
报告人简介：
李尧，马萨诸塞大学数学与统计系副教授，研究领域为应用动力系统及相关随机计算，近年来在数据驱动的科学计算、数学物理、生物神经网络以及机器学习等方面取得诸多重要成果，研究工作发表在Communications on Pure and Applied Mathematics，Archive for Rational Mechanics and Analysis，Annals of Applied Probability 等国际重要期刊。
