Model reduction by separation of variables: a comparison between Hierarchical Model reduction and Proper Generalized Decomposition
Thursday 13th December 2018
Perotto, S.; Carlino, M.G.; Ballarin, F.
Hierarchical Model reduction and Proper Generalized Decomposition both exploit separation of variables to perform a model reduction. After setting the basics, we exemplify these techniques on some standard elliptic problems to highlight pros and cons of the two procedures, both from a methodological and a numerical viewpoint.