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Nicola Demo
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2020 – today
- 2024
- [j12]Davide Roznowicz, Giovanni Stabile, Nicola Demo, Davide Fransos, Gianluigi Rozza:
Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics. Adv. Model. Simul. Eng. Sci. 11(1): 6 (2024) - [i18]Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo, Marco Tezzele, Karl Lapo, Gianluigi Rozza, Steven L. Brunton, J. Nathan Kutz:
PyDMD: A Python package for robust dynamic mode decomposition. CoRR abs/2402.07463 (2024) - 2023
- [j11]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
A DeepONet multi-fidelity approach for residual learning in reduced order modeling. Adv. Model. Simul. Eng. Sci. 10(1): 12 (2023) - [j10]Laura Meneghetti, Nicola Demo, Gianluigi Rozza:
A dimensionality reduction approach for convolutional neural networks. Appl. Intell. 53(19): 22818-22833 (2023) - [j9]Nicola Demo, Maria Strazzullo, Gianluigi Rozza:
An extended physics informed neural network for preliminary analysis of parametric optimal control problems. Comput. Math. Appl. 143: 383-396 (2023) - [j8]Dario Coscia, Anna Ivagnes, Nicola Demo, Gianluigi Rozza:
Physics-Informed Neural networks for Advanced modeling. J. Open Source Softw. 8(87): 5352 (2023) - [j7]Anna Ivagnes, Nicola Demo, Gianluigi Rozza:
Towards a Machine Learning Pipeline in Reduced Order Modelling for Inverse Problems: Neural Networks for Boundary Parametrization, Dimensionality Reduction and Solution Manifold Approximation. J. Sci. Comput. 95(1): 23 (2023) - [j6]Francesco Andreuzzi, Nicola Demo, Gianluigi Rozza:
A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems. SIAM J. Appl. Dyn. Syst. 22(3): 2432-2458 (2023) - [i17]Martina Teruzzi, Nicola Demo, Gianluigi Rozza:
A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration. CoRR abs/2302.06473 (2023) - [i16]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
A DeepONet Multi-Fidelity Approach for Residual Learning in Reduced Order Modeling. CoRR abs/2302.12682 (2023) - [i15]Anna Ivagnes, Nicola Demo, Gianluigi Rozza:
A shape optimization pipeline for marine propellers by means of reduced order modeling techniques. CoRR abs/2305.07515 (2023) - [i14]Dario Coscia, Nicola Demo, Gianluigi Rozza:
Generative Adversarial Reduced Order Modelling. CoRR abs/2305.15881 (2023) - 2022
- [c2]Laura Meneghetti, Nicola Demo, Gianluigi Rozza:
A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks. ICIP 2022: 2206-2210 - [i13]Laura Meneghetti, Nicola Demo, Gianluigi Rozza:
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks. CoRR abs/2207.13551 (2022) - [i12]Dario Coscia, Laura Meneghetti, Nicola Demo, Giovanni Stabile, Gianluigi Rozza:
A Continuous Convolutional Trainable Filter for Modelling Unstructured Data. CoRR abs/2210.13416 (2022) - [i11]Anna Ivagnes, Nicola Demo, Gianluigi Rozza:
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation. CoRR abs/2210.14764 (2022) - 2021
- [j5]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems. SIAM J. Sci. Comput. 43(3): B831-B853 (2021) - [j4]Marco Tezzele, Nicola Demo, Andrea Mola, Gianluigi Rozza:
PyGeM: Python Geometrical Morphing. Softw. Impacts 7: 100047 (2021) - [i10]Nicola Demo, Marco Tezzele, Andrea Mola, Gianluigi Rozza:
Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing. CoRR abs/2101.03781 (2021) - [i9]Davide Papapicco, Nicola Demo, Michele Girfoglio, Giovanni Stabile, Gianluigi Rozza:
The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations. CoRR abs/2108.06558 (2021) - [i8]Francesco Andreuzzi, Nicola Demo, Gianluigi Rozza:
A dynamic mode decomposition extension for the forecasting of parametric dynamical systems. CoRR abs/2110.09155 (2021) - [i7]Laura Meneghetti, Nicola Demo, Gianluigi Rozza:
A Dimensionality Reduction Approach for Convolutional Neural Networks. CoRR abs/2110.09163 (2021) - [i6]Nicola Demo, Maria Strazzullo, Gianluigi Rozza:
An extended physics informed neural network for preliminary analysis of parametric optimal control problems. CoRR abs/2110.13530 (2021) - 2020
- [j3]Marco Tezzele, Nicola Demo, Giovanni Stabile, Andrea Mola, Gianluigi Rozza:
Enhancing CFD predictions in shape design problems by model and parameter space reduction. Adv. Model. Simul. Eng. Sci. 7(1): 40 (2020) - [i5]Marco Tezzele, Nicola Demo, Giovanni Stabile, Andrea Mola, Gianluigi Rozza:
Enhancing CFD predictions in shape design problems by model and parameter space reduction. CoRR abs/2001.05237 (2020) - [i4]Nicola Demo, Giulio Ortali, Gianluca Gustin, Gianluigi Rozza, Gianpiero Lavini:
An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques. CoRR abs/2004.11201 (2020) - [i3]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
A supervised learning approach involving active subspaces for an efficient genetic algorithm in high-dimensional optimization problems. CoRR abs/2006.07282 (2020) - [i2]Giulio Ortali, Nicola Demo, Gianluigi Rozza:
Gaussian process approach within a data-driven POD framework for fluid dynamics engineering problems. CoRR abs/2012.01989 (2020)
2010 – 2019
- 2019
- [i1]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
A non-intrusive approach for proper orthogonal decomposition modal coefficients reconstruction through active subspaces. CoRR abs/1907.12777 (2019) - 2018
- [j2]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
PyDMD: Python Dynamic Mode Decomposition. J. Open Source Softw. 3(22): 530 (2018) - [j1]Nicola Demo, Marco Tezzele, Gianluigi Rozza:
EZyRB: Easy Reduced Basis method. J. Open Source Softw. 3(24): 661 (2018) - 2015
- [c1]Enrico Calore, Nicola Demo, Sebastiano Fabio Schifano, Raffaele Tripiccione:
Experience on Vectorizing Lattice Boltzmann Kernels for Multi- and Many-Core Architectures. PPAM (1) 2015: 53-62
Coauthor Index
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last updated on 2024-04-16 23:12 CEST by the dblp team
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