Computational Inverse Problems


Laurent Demanet, MIT, visiting UCLouvain

Schedule and place

This 15-hour course will take place in 10 sessions over five days on November 13,15,18,20,27, 2019

at UCLouvain - Euler building (room A.002) Avenue Georges Lemaître,4 - 1348 Louvain la Neuve (November 13,15,18) and Maxwell building (November 20 and 27) Shannon room, (A105), Place du Levant 3 - 1348 Louvain-la-Neuve 

Schedule: 3 hours/day, from 11:00 to 12:30 and from 14:00 to 15:30  

Travel instructions are available here


Abstract: A broad overview of mathematical and computational methods for inverse problems, with applications in data sciences, physical sciences, and imaging from remote sensing. The course assumes some affinity with undergraduate mathematics, but is otherwise suited to graduate students from all majors/orientations. Topics: Regression, regularization, and convex optimization. Duality and recovery theory for sparse regression and matrix completion. Maximum likelihood estimation and the Bayesian framework. Iterative methods for smooth optimization. Proximal and primal-dual iterative schemes for nonsmooth optimization. If time permits, algebraic methods of superresolution.

Course material

To be determined


To be determined.