Experience on Vectorizing Lattice Boltzmann Kernels for Multi- and Many-Core Architectures. - Enrico Calore; Nicola Demo; Sebastiano Fabio Schifano; Raffaele Tripiccione (PPAM (1), 2015)

PyDMD: Python Dynamic Mode Decomposition. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (J. Open Source Softw., 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (J. Open Source Softw., 2018)

PyDMD: Python Dynamic Mode Decomposition. - Marco Tezzele; Nicola Demo; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2018)

A non-intrusive approach for proper orthogonal decomposition modal coefficients reconstruction through active subspaces. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (CoRR, 2019)

Enhancing CFD predictions in shape design problems by model and parameter space reduction. - Marco Tezzele; Nicola Demo; Giovanni Stabile; Andrea Mola; Gianluigi Rozza (Adv. Model. Simul. Eng. Sci., 2020)

An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques. - Nicola Demo; Giulio Ortali; Gianluca Gustin; Gianluigi Rozza; Gianpiero Lavini (CoRR, 2020)

Gaussian process approach within a data-driven POD framework for fluid dynamics engineering problems. - Giulio Ortali; Nicola Demo; Gianluigi Rozza (CoRR, 2020)

Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing. - Nicola Demo; Marco Tezzele; Andrea Mola; Gianluigi Rozza (CoRR, 2021)

The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations. - Davide Papapicco; Nicola Demo; Michele Girfoglio; Giovanni Stabile; Gianluigi Rozza (CoRR, 2021)

A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (SIAM J. Sci. Comput., 2021)

PyGeM: Python Geometrical Morphing. - Marco Tezzele; Nicola Demo; Andrea Mola; Gianluigi Rozza (Softw. Impacts, 2021)

A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks. - Laura Meneghetti; Nicola Demo; Gianluigi Rozza (ICIP, 2022)

A Continuous Convolutional Trainable Filter for Modelling Unstructured Data. - Dario Coscia; Laura Meneghetti; Nicola Demo; Giovanni Stabile; Gianluigi Rozza (CoRR, 2022)

An extended physics informed neural network for preliminary analysis of parametric optimal control problems. - Nicola Demo; Maria Strazzullo; Gianluigi Rozza (Comput. Math. Appl., 2023)

A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration. - Martina Teruzzi; Nicola Demo; Gianluigi Rozza (CoRR, 2023)

A shape optimization pipeline for marine propellers by means of reduced order modeling techniques. - Anna Ivagnes; Nicola Demo; Gianluigi Rozza (CoRR, 2023)

Generative Adversarial Reduced Order Modelling. - Dario Coscia; Nicola Demo; Gianluigi Rozza (CoRR, 2023)

Physics-Informed Neural networks for Advanced modeling. - Dario Coscia; Anna Ivagnes; Nicola Demo; Gianluigi Rozza (J. Open Source Softw., 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

Towards a Machine Learning Pipeline in Reduced Order Modelling for Inverse Problems: Neural Networks for Boundary Parametrization, Dimensionality Reduction and Solution Manifold Approximation. - Anna Ivagnes; Nicola Demo; Gianluigi Rozza (J. Sci. Comput., 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

PINA: Physics-Informed Neural networks for Advanced modeling. - Dario Coscia; Anna Ivagnes; Nicola Demo; Gianluigi Rozza (Zenodo, 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems. - Francesco Andreuzzi; Nicola Demo; Gianluigi Rozza (SIAM J. Appl. Dyn. Syst., 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

A dimensionality reduction approach for convolutional neural networks. - Laura Meneghetti; Nicola Demo; Gianluigi Rozza (Appl. Intell., 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2023)

A DeepONet multi-fidelity approach for residual learning in reduced order modeling. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Adv. Model. Simul. Eng. Sci., 2023)

PyDMD: A Python package for robust dynamic mode decomposition. - Sara M. Ichinaga; Francesco Andreuzzi; Nicola Demo; Marco Tezzele; Karl Lapo; Gianluigi Rozza; Steven L. Brunton; J. Nathan Kutz (CoRR, 2024)

Non-intrusive model reduction of advection-dominated hyperbolic problems using neural network shift augmented manifold transformations. - Harshith Gowrachari; Nicola Demo; Giovanni Stabile; Gianluigi Rozza (CoRR, 2024)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2024)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2024)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2024)

EZyRB: Easy Reduced Basis method. - Nicola Demo; Marco Tezzele; Gianluigi Rozza (Zenodo, 2024)

Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics. - Davide Roznowicz; Giovanni Stabile; Nicola Demo; Davide Fransos; Gianluigi Rozza (Adv. Model. Simul. Eng. Sci., 2024)

KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition. - Laura Meneghetti; Edoardo Bianchi; Nicola Demo; Gianluigi Rozza (DASIP, 2025)

Data-driven discovery of delay differential equations with discrete delays. - Alessandro Pecile; Nicola Demo; Marco Tezzele; Gianluigi Rozza; Dimitri Breda (J. Comput. Appl. Math., 2025)

BARNN: A Bayesian Autoregressive and Recurrent Neural Network. - Dario Coscia; Max Welling; Nicola Demo; Gianluigi Rozza (CoRR, 2025)

Machine Learning-based quadratic closures for non-intrusive Reduced Order Models. - Gabriele Codega; Anna Ivagnes; Nicola Demo; Gianluigi Rozza (CoRR, 2025)