报告题目：From Model to Data driven Imaging Inverse problems

报 告 人：张小群教授（上海交通大学）

报告时间：2024年5月10日  15:30-16:30

报告地点：腾讯会议（895-348-843）

报告摘要：

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 both the computational and theoretical aspects for solving the related large-scale variational problems and Bayesian sampling methods.

报告人简介：

张小群，上海交通大学特聘教授。主要研究方向：图像科学、医学图像处理、数据科学等问题中的数学模型与计算方法。现任Inverse Problems and Imaging、CSIAM-AM、Journal on Mathematical Imaging and Vision杂志编委，CSIAM大数据与人工智能专委会、数学与医学交叉学科专业委员会委员。