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Scientific Machine Learning Through Physics-Informed Neural Networks: Where we are and What's Next.

, , , , , and . J. Sci. Comput., 92 (3): 88 (2022)

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A Reduced-Order Strategy for Solving Inverse Bayesian Shape Identification Problems in Physiological Flows., , , and . HPSC, page 145-155. Springer, (2012)On a Certified Smagorinsky Reduced Basis Turbulence Model., , , , and . SIAM J. Numer. Anal., 55 (6): 3047-3067 (2017)Model Reduction for Parametrized Optimal Control Problems in Environmental Marine Sciences and Engineering., , , and . SIAM J. Sci. Comput., 40 (4): B1055-B1079 (2018)Non-intrusive PODI-ROM for patient-specific aortic blood flow in presence of a LVAD device., , , , , , , , and . CoRR, (2020)POD-Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation., , and . J. Sci. Comput., 83 (3): 55 (2020)A Reduced Order technique to study bifurcating phenomena: application to the Gross-Pitaevskii equation., , and . CoRR, (2019)A Reduced-Order Shifted Boundary Method for Parametrized incompressible Navier-Stokes equations., , , , and . CoRR, (2019)POD-Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation., , and . CoRR, (2019)Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization., , , , , , and . J. Comput. Phys., (2016)Model Order Reduction for Deforming Domain Problems in a Time-Continuous Space-Time Setting., , , and . CoRR, (2023)