Demo, Nicola

Demo, Nicola  

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Titolo Data di pubblicazione Autori File
A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems 1-gen-2019 Nicola DemoMarco TezzeleAndrea MolaGianluigi Rozza
A continuous convolutional trainable filter for modelling unstructured data 1-gen-2023 Coscia, DMeneghetti, LDemo, NStabile, GRozza, G
A dimensionality reduction approach for convolutional neural networks 1-gen-2023 Meneghetti, LDemo, NRozza, G
A Gaussian Process Regression approach within a data-driven POD framework for engineering problems in fluid dynamics 1-gen-2022 Giulio OrtaliNicola DemoGianluigi Rozza
A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces 1-gen-2019 Nicola DemoMarco TezzeleGianluigi Rozza
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks 1-gen-2022 Meneghetti, L.Demo, N.Rozza, G.
A supervised learning approach involving active subspaces for an efficient genetic algorithm in high-dimensional optimization problems 1-gen-2021 Demo N.Tezzele M.Rozza G.
Advances in reduced order methods for parametric industrial problems in computational fluid dynamics 1-gen-2018 Rozza, GianluigiMalik, HarisDemo, NicolaTezzele, MarcoGirfoglio, MicheleStabile, GiovanniMola, Andrea
An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques 1-gen-2021 Nicola DemoGiulio OrtaliGianluigi Rozza +
An efficient shape parametrisation by free-form deformation enhanced by active subspace for hull hydrodynamic ship design problems in open source environment 1-gen-2018 Demo, NicolaTezzele, MarcoMola, AndreaRozza, Gianluigi
An integrated data-driven computational pipeline with model order reduction for industrial and applied mathematics 1-gen-2022 Tezzele, MarcoDemo, NicolaMola, AndreaRozza, Gianluigi
Chapter 20: A Deep Learning Approach to Improving Reduced Order Models 1-gen-2022 Meneghetti, LauraShah, NiravGirfoglio, MicheleDemo, NicolaTezzele, MarcoLario, AndreaStabile, GiovanniRozza, Gianluigi
Enhancing CFD predictions in shape design problems by model and parameter space reduction 1-gen-2020 Tezzele M.Demo N.Stabile G.Mola A.Rozza G.
Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing 1-gen-2021 Nicola DemoMarco TezzeleAndrea MolaGianluigi Rozza
Increasing speedup of naval hull workflow optimization using Reduced Order Methods 16-dic-2016 Demo, Nicola
Model order reduction by means of active subspaces and dynamic mode decomposition for parametric hull shape design hydrodynamics 1-gen-2018 Tezzele, MarcoDemo, NicolaGADALLA, Mahmoud Gamal Ali SalemMola, AndreaRozza, Gianluigi
PyGeM: Python Geometrical Morphing 1-gen-2021 Tezzele, M.Demo, N.Mola, A.Rozza, G.
Reduced order isogeometric analysis approach for PDEs in parametrized domains 1-gen-2020 Garotta F.Demo N.Tezzele M.Reali A.Rozza G. +
Shape Optimization by means of Proper Orthogonal Decomposition and Dynamic Mode Decomposition 1-gen-2018 Demo, NicolaTezzele, MarcoRozza, Gianluigi +
Shape optimization through proper orthogonal decomposition with interpolation and dynamic mode decomposition enhanced by active subspaces 1-gen-2019 Tezzele MarcoDemo NicolaRozza Gianluigi