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D
Hess MW, Quaini A, Rozza G. Data-Driven Enhanced Model Reduction for Bifurcating Models in Computational Fluid Dynamics. 2022 .
Donadini E, Strazzullo M, Tezzele M, Rozza G. A data-driven partitioned approach for the resolution of time-dependent optimal control problems with dynamic mode decomposition. 2021 .
Hijazi S, Stabile G, Mola A, Rozza G. Data-driven POD-Galerkin reduced order model for turbulent flows. Journal of Computational Physics [Internet]. 2020 ;416:109513. Available from: https://arxiv.org/abs/1907.09909
Hess MW, Quaini A, Rozza G. A Data-Driven Surrogate Modeling Approach for Time-Dependent Incompressible Navier-Stokes Equations with Dynamic Mode Decomposition and Manifold Interpolation. 2022 .
Arndt D, Bangerth W, Blais B, Clevenger TC, Fehling M, Grayver AV, Heister T, Heltai L, Kronbichler M, Maier M, et al. The deal.II library, Version 9.2. Journal of Numerical Mathematics. 2020 ;28:131–146.
Ruziboev M. Decay of correlations for invertible maps with non-Hölder observables. Dynamical Systems [Internet]. 2015 ;30:341-352. Available from: https://doi.org/10.1080/14689367.2015.1046816
Soranzo N, Ramezani F, Iacono G, Altafini C. Decompositions of large-scale biological systems based on dynamical properties. Bioinformatics (Oxford, England). 2012 Jan; 28(1):76-83 [Internet]. 2012 . Available from: http://hdl.handle.net/1963/5226
Amelino-Camelia G, Marciano A, Matassa M, Rosati G. Deformed Lorentz symmetry and relative locality in a curved/expanding spacetime. Phys. Rev. D 86 (2012) 124035. 2012 .
Bressan A, Rampazzo F. On differential systems with vector-valued impulsive controls. Boll. Un. Mat. Ital. B (7) 2 (1988), no. 3, 641-656 [Internet]. 1988 . Available from: http://hdl.handle.net/1963/535
Tezzele M, Salmoiraghi F, Mola A, Rozza G. Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems. Advanced Modeling and Simulation in Engineering Sciences. 2018 ;5:25.
Meneghetti L, Demo N, Rozza G. A Dimensionality Reduction Approach for Convolutional Neural Networks. 2021 .
Shah N, Hess MW, Rozza G. Discontinuous Galerkin Model Order Reduction of Geometrically Parametrized Stokes Equation. In: Vermolen FJ, Vuik C Numerical Mathematics and Advanced Applications ENUMATH 2019. Numerical Mathematics and Advanced Applications ENUMATH 2019. Cham: Springer International Publishing; 2021.
Pichi F, Strazzullo M, Ballarin F, Rozza G. Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction. ESAIM: M2AN [Internet]. 2022 ;56(4):1361 - 1400. Available from: https://doi.org/10.1051/m2an/2022044
Andreuzzi F, Demo N, Rozza G. A dynamic mode decomposition extension for the forecasting of parametric dynamical systems. arXiv preprint arXiv:2110.09155. 2021 .
E
Pintore M, Pichi F, Hess MW, Rozza G, Canuto C. Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method. Advances in Computational Mathematics [Internet]. 2020 . Available from: https://arxiv.org/abs/1912.06089
Pintore M, Pichi F, Hess MW, Rozza G, Canuto C. Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method. Advances in Computational Mathematics. 2021 ;47.
Demo N, Ortali G, Gustin G, Rozza G, Lavini G. An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques. Bolletino dell Unione Matematica Italiana. 2021 ;14:211-230.
Forti D, Rozza G. Efficient geometrical parametrisation techniques of interfaces for reduced-order modelling: application to fluid–structure interaction coupling problems. International Journal of Computational Fluid Dynamics. 2014 ;28:158–169.
Stabile G, Zancanaro M, Rozza G. Efficient Geometrical parametrization for finite-volume based reduced order methods. International Journal for Numerical Methods in Engineering [Internet]. 2020 ;121:2655-2682. Available from: https://arxiv.org/abs/1901.06373

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