Nicola Demo
Orcid: 0000-0003-3107-9738
According to our database1,
Nicola Demo
authored at least 24 papers
between 2015 and 2024.
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Bibliography
2024
Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics.
Adv. Model. Simul. Eng. Sci., December, 2024
2023
Adv. Model. Simul. Eng. Sci., December, 2023
Appl. Intell., October, 2023
A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems.
SIAM J. Appl. Dyn. Syst., September, 2023
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., April, 2023
A shape optimization pipeline for marine propellers by means of reduced order modeling techniques.
CoRR, 2023
A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration.
CoRR, 2023
An extended physics informed neural network for preliminary analysis of parametric optimal control problems.
Comput. Math. Appl., 2023
2022
CoRR, 2022
A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
2021
A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems.
SIAM J. Sci. Comput., 2021
The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations.
CoRR, 2021
Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing.
CoRR, 2021
2020
Gaussian process approach within a data-driven POD framework for fluid dynamics engineering problems.
CoRR, 2020
An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques.
CoRR, 2020
Enhancing CFD predictions in shape design problems by model and parameter space reduction.
Adv. Model. Simul. Eng. Sci., 2020
2019
A non-intrusive approach for proper orthogonal decomposition modal coefficients reconstruction through active subspaces.
CoRR, 2019
2018
2015
Experience on Vectorizing Lattice Boltzmann Kernels for Multi- and Many-Core Architectures.
Proceedings of the Parallel Processing and Applied Mathematics, 2015