【Academic Seminar】The Applications of Empirical Process in the Uncertainty Quantification Driven by PDE Problems with Observational Data
Topic: The Applications of Empirical Process in the Uncertainty Quantification Driven by PDE Problems with Observational Data
Time & Date: 10:30 - 11:30 am, Wednesday, April 21, 2021
Venue: Room 101, Zhi Xin Building
Speaker: Prof. Wenlong ZHANG, Southern University of Science and Technology, Department of Mathematics
Zoom Meeting ID: 559 916 3678 (Passcode: 962062)
For many real applications, the data needed for computation is mixed by random noise or random field, this is the so called uncertainty quantification(UQ). In this talk, I will show some new research in the uncertainty quantification driven by PDE problems including theory and numerical examples. The observational data in practice is always blurred by some noise, e.g. natural noise, the error of the measurements and the error of the model itself. For years, it's a challenge to recover the true information from noisy data in many fields. In this talk I will give new analytical tools to estimate the stochastic convergence in some problems driven by PDE using regularization method. It provides the optimal parameter choices in the models and the stochastic error estimates are given therein. Several applications will be shown in this talk.
Zhang Wenlong, got PHD from Ecole Normale Superieure, Paris and now is an assistant professor in SUSTech. His research interests include inverse problems, uncertainty quantification, numerical analysis, he has published several papers on journals Siam and inverse problems.