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Rozza G, Huynh P, Manzoni A. Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants. Numerische Mathematik, 2013 [Internet]. 2013 . Available from: http://hdl.handle.net/1963/6339
Rozza G, Manzoni A, Negri F. Reduction strategies for PDE-constrained oprimization problems in Haemodynamics. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012) J. Eberhardsteiner et.al. (eds.), Vienna, Austria, 10-14 sept. 2012 [Internet]. 2012 . Available from: http://hdl.handle.net/1963/6338
Rozza G. Fundamentals of Reduced Basis Method for problems governed by parametrized PDEs and applications. In: Separated representations and PGD-based model reduction : fundamentals and applications. Vol. 554. Separated representations and PGD-based model reduction : fundamentals and applications. Wien: Springer; 2014.
Rozza G, Chen P, Quarteroni A. Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations. Numerische Mathematik, (2015), 36 p. Article in Press [Internet]. 2015 . Available from: http://urania.sissa.it/xmlui/handle/1963/34491
Rozza G, Malik MH, Demo N, Tezzele M, Girfoglio M, Stabile G, Mola A. Advances in reduced order methods for parametric industrial problems in computational fluid dynamics. In: Proceedings of the 6th European Conference on Computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th European Conference on Computational Fluid Dynamics, ECFD 2018. Proceedings of the 6th European Conference on Computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th European Conference on Computational Fluid Dynamics, ECFD 2018. ; 2020. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075395686&partnerID=40&md5=fb0b1a3cfdfd35a104db9921bc9be675
Rozza G, Hess MW, Stabile G, Tezzele M, Ballarin F. Basic ideas and tools for projection-based model reduction of parametric partial differential equations. In: Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms. Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms. Berlin, Boston: De Gruyter; 2020. pp. 1 - 47. Available from: https://www.degruyter.com/view/book/9783110671490/10.1515/9783110671490-001.xml

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