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.
CITATION STYLE
Perotto, S., Carlino, M. G., & Ballarin, F. (2020). Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition. In Lecture Notes in Computational Science and Engineering (Vol. 134, pp. 61–77). Springer. https://doi.org/10.1007/978-3-030-39647-3_4
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