报告题目 (Title)：Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems（大尺度反问题的混合投影法）
报告人 (Speaker)：姜嘉骅 助理教授（伯明翰大学）
报告时间 (Time)：2024年4月26日 (周五) 10:00
报告地点 (Place)：校本部GJ403
邀请人(Inviter)：纪丽洁
主办部门：古天乐代言太阳集团数学系
摘要：We develop hybrid projection methods for computing solutions to large-scale inverse problems, where the solution represents a sum of different stochastic components. Such scenarios arise in many imaging applications where the reconstructed solution can be represented as a combination of two or more components and each component contains different smoothness or stochastic properties. We focus on the scenario where the solution is a sum of a sparse solution and a smooth solution. For computing solution estimates, we develop hybrid projection methods for solution decomposition that are based on a combined flexible and generalized Golub–Kahan process. Numerical results from photoacoustic tomography and atmospheric inverse modeling demonstrate the potential for these methods to be used for anomaly detection.
