Seminar| Institute of Mathematical Sciences
Time: Thursday, January 18th, 2024 , 10:15-11:15
Location:RS408, IMS
Speaker: Xiaoqun Zhang, Shanghai Jiao Tong University
Abstract: Imaging from downsampled and corrupted measurements are mathematically ill-posed inverse problems. In this talk, I will discuss two paradigms: model and data driven, especially sparsity and deep learning-based methods for solving linear and nonlinear imaging inverse problems. I will also discuss the computational aspects for solving the related large-scale variational problems and Bayesian sampling methods as well as the theoretical results.