News & Events
Speaker: Yan Liang, PhD supervisor, Southeast University
Date: August 25, 2023
Location: Tencent Meeting
Sponsor: School of Mathematics, Shandong University
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.
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