Speaker: Yan Liang, PhD supervisor, Southeast University

Date: August 25, 2023

Time: 9:00-10:30

Location: Tencent Meeting

Sponsor: School of Mathematics, Shandong University

Abstract:

Obtaining samples from the posterior distribution of Bayesian inverse problems is a long-standing challenge, especially when the forward operator is modelled by a partial differential equation (PDE). In this talk, we will discuss how to leverage deep learning's capabilities to tackle this challenge. Several fast and efficient deep neural network (DNN)-based approaches for accelerating simulations in sample generation will be described. A novel framework based on invertible neural networks using normalizing flow is also demonstrated.

For more information, please visit:

https://www.view.sdu.edu.cn/info/1020/182904.htm