報告題目：Data-driven computational methods for stochastic dynamics
報 告 人：李堯副 教授
所在單位：馬薩諸塞大學
報告時間：2024年7月12 日 星期五 上午 10:00 - 11：00
報告地點： 數學樓第一報告廳
校内聯系人：王式柔 shirou@jlu.edu.cn
報告摘要： 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.
報告人簡介：
李堯，馬薩諸塞大學數學與統計系副教授，研究領域為應用動力系統及相關随機計算，近年來在數據驅動的科學計算、數學物理、生物神經網絡以及機器學習等方面取得諸多重要成果，研究工作發表在Communications on Pure and Applied Mathematics，Archive for Rational Mechanics and Analysis，Annals of Applied Probability 等國際重要期刊。
