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. POD–Galerkin reduced order methods for combined Navier–Stokes transport equations based on a hybrid FV-FE solver. Computers and Mathematics with Applications [Internet]. 2020 ;79:256-273. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068068567&doi=10.1016%2fj.camwa.2019.06.026&partnerID=40&md5=a8dcce1b53b8ee872d174bbc4c20caa3
. Projection-based reduced order models for a cut finite element method in parametrized domains. Computers and Mathematics with Applications [Internet]. 2020 ;79:833-851. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070900852&doi=10.1016%2fj.camwa.2019.08.003&partnerID=40&md5=2d222ab9c7832955d155655d3c93e1b1
. A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks. In: 2022 IEEE International Conference on Image Processing (ICIP). 2022 IEEE International Conference on Image Processing (ICIP). ; 2022.
. PyDMD: Python Dynamic Mode Decomposition. The Journal of Open Source Software [Internet]. 2018 ;3:530. Available from: https://joss.theoj.org/papers/734e4326edd5062c6e8ee98d03df9e1d
. PyGeM: Python Geometrical Morphing. Software Impacts. 2021 ;7:100047.
. A Reduced Basis Approach for Modeling the Movement of Nuclear Reactor Control Rods. NERS-14-1062; ASME J of Nuclear Rad Sci, 2, 2 (2016) 021019 [Internet]. 2016 ;2(2):8. Available from: http://urania.sissa.it/xmlui/handle/1963/35192
. A reduced basis approach for PDEs on parametrized geometries based on the shifted boundary finite element method and application to a Stokes flow. Computer Methods in Applied Mechanics and Engineering [Internet]. 2019 ;347:568-587. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060107322&doi=10.1016%2fj.cma.2018.12.040&partnerID=40&md5=1a3234f0cb000c91494d946428f8ebef
. Reduced basis approaches for parametrized bifurcation problems held by non-linear Von Kármán equations. [Internet]. 2019 ;81:112–135. Available from: https://arxiv.org/abs/1804.02014
. Reduced Basis Approaches for Parametrized Bifurcation Problems held by Non-linear Von Kármán Equations. Journal of Scientific Computing [Internet]. 2019 ;81:112-135. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068973907&doi=10.1007%2fs10915-019-01003-3&partnerID=40&md5=a09af83ce45183d6965cdb79d87a919b
. Reduced basis approaches in time-dependent noncoercive settings for modelling the movement of nuclear reactor control rods. Communications in Computational Physics [Internet]. 2016 ;(in press). Available from: http://urania.sissa.it/xmlui/handle/1963/34963
. Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings. In: Numerical Methods for PDEs. Vol. 15. Numerical Methods for PDEs. ; 2018. Available from: https://link.springer.com/chapter/10.1007/978-3-319-94676-4_8
. Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings. SEMA SIMAI Springer Series [Internet]. 2018 ;15:203-247. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055036627&doi=10.1007%2f978-3-319-94676-4_8&partnerID=40&md5=e9c07038e7bcc6668ec702c0653410dc
. 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
. Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system. Advances in Computational Mathematics. 2015 ;special issue for MoRePaS 2012(in press).
. Reduced Basis Approximation for the Structural-Acoustic Design based on Energy Finite Element Analysis (RB-EFEA). In: CEMRACS 2013 - Modelling and simulation of complex systems: stochastic and deterministic approaches. Vol. 48. CEMRACS 2013 - Modelling and simulation of complex systems: stochastic and deterministic approaches. ; 2013. pp. 98-115.
. Reduced basis approximation of parametrized advection-diffusion PDEs with high Péclet number. Lecture Notes in Computational Science and Engineering. 2015 ;103:419–426.
. Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations. Computers and Mathematics with Applications. 2015 ;69:319–336.
. Reduced basis method and domain decomposition for elliptic problems in networks and complex parametrized geometries. Computers and Mathematics with Applications . 2016 ;71(1):430.
. Reduced basis method for parametrized elliptic optimal control problems. SIAM Journal on Scientific Computing. 2013 ;35:A2316–A2340.
. Reduced basis method for the Stokes equations in decomposable domains using greedy optimization. In: ECMI 2014 proceedings. ECMI 2014 proceedings. ; 2014. pp. 1–7.
. Reduced Basis Methods for Uncertainty Quantification. SIAM/ASA Journal on Uncertainty Quantification. 2017 ;5(1):869.
. Reduced Basis Model Order Reduction for Navier-Stokes equations in domains with walls of varying curvature. International Journal of Computational Fluid Dynamics [Internet]. 2020 ;34:119-126. Available from: https://arxiv.org/abs/1901.03708
. Reduced basis model order reduction for Navier–Stokes equations in domains with walls of varying curvature. International Journal of Computational Fluid Dynamics [Internet]. 2020 ;34:119-126. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085233294&doi=10.1080%2f10618562.2019.1645328&partnerID=40&md5=e2ed8f24c66376cdc8b5485aa400efb0