Nicola Demo - RankMe

41 papers A* 1B 1Journal 37Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Plug-and-play neural compression: A knowledge distillation framework with flexible dimensionality reduction. J. Syst. Archit. Laura Meneghetti, Edoardo Bianchi, Nicola Demo, Gianluigi Rozza
2025	A*	`conf`	BARNN: A Bayesian Autoregressive and Recurrent Neural Network. ICML Dario Coscia, Max Welling, Nicola Demo, Gianluigi Rozza
2025	J	`jnl`	BARNN: A Bayesian Autoregressive and Recurrent Neural Network. CoRR Dario Coscia, Max Welling, Nicola Demo, Gianluigi Rozza
2025	J	`jnl`	Data-driven discovery of delay differential equations with discrete delays. J. Comput. Appl. Math. Alessandro Pecile, Nicola Demo, Marco Tezzele, Gianluigi Rozza, Dimitri Breda
2025	—	`conf`	KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition. DASIP Laura Meneghetti, Edoardo Bianchi, Nicola Demo, Gianluigi Rozza
2025	J	`jnl`	Machine Learning-based quadratic closures for non-intrusive Reduced Order Models. CoRR Gabriele Codega, Anna Ivagnes, Nicola Demo, Gianluigi Rozza
2024	J	`jnl`	Data-driven Discovery of Delay Differential Equations with Discrete Delays. CoRR Alessandro Pecile, Nicola Demo, Marco Tezzele, Gianluigi Rozza, Dimitri Breda
2024	J	`jnl`	Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics. Adv. Model. Simul. Eng. Sci. Davide Roznowicz, Giovanni Stabile, Nicola Demo, Davide Fransos, Gianluigi Rozza
2024	J	`jnl`	Non-intrusive model reduction of advection-dominated hyperbolic problems using neural network shift augmented manifold transformations. CoRR Harshith Gowrachari, Nicola Demo, Giovanni Stabile, Gianluigi Rozza
2024	J	`jnl`	PyDMD: A Python Package for Robust Dynamic Mode Decomposition. J. Mach. Learn. Res. Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo, Marco Tezzele, Karl Lapo, Gianluigi Rozza, Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	PyDMD: A Python package for robust dynamic mode decomposition. CoRR Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo, Marco Tezzele, Karl Lapo, Gianluigi Rozza, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	A DeepONet Multi-Fidelity Approach for Residual Learning in Reduced Order Modeling. CoRR Nicola Demo, Marco Tezzele, Gianluigi Rozza
2023	J	`jnl`	A DeepONet multi-fidelity approach for residual learning in reduced order modeling. Adv. Model. Simul. Eng. Sci. Nicola Demo, Marco Tezzele, Gianluigi Rozza
2023	J	`jnl`	A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems. SIAM J. Appl. Dyn. Syst. Francesco Andreuzzi, Nicola Demo, Gianluigi Rozza
2023	J	`jnl`	A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration. CoRR Martina Teruzzi, Nicola Demo, Gianluigi Rozza
2023	J	`jnl`	A dimensionality reduction approach for convolutional neural networks. Appl. Intell. Laura Meneghetti, Nicola Demo, Gianluigi Rozza
2023	J	`jnl`	A shape optimization pipeline for marine propellers by means of reduced order modeling techniques. CoRR Anna Ivagnes, Nicola Demo, Gianluigi Rozza
2023	J	`jnl`	An extended physics informed neural network for preliminary analysis of parametric optimal control problems. Comput. Math. Appl. Nicola Demo, Maria Strazzullo, Gianluigi Rozza
2023	J	`jnl`	Generative Adversarial Reduced Order Modelling. CoRR Dario Coscia, Nicola Demo, Gianluigi Rozza
2023	J	`jnl`	Physics-Informed Neural networks for Advanced modeling. J. Open Source Softw. Dario Coscia, Anna Ivagnes, Nicola Demo, Gianluigi Rozza
2023	J	`jnl`	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. Anna Ivagnes, Nicola Demo, Gianluigi Rozza
2022	J	`jnl`	A Continuous Convolutional Trainable Filter for Modelling Unstructured Data. CoRR Dario Coscia, Laura Meneghetti, Nicola Demo, Giovanni Stabile, Gianluigi Rozza
2022	B	`conf`	A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks. ICIP Laura Meneghetti, Nicola Demo, Gianluigi Rozza
2022	J	`jnl`	A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks. CoRR Laura Meneghetti, Nicola Demo, Gianluigi Rozza
2022	J	`jnl`	Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation. CoRR Anna Ivagnes, Nicola Demo, Gianluigi Rozza
2021	J	`jnl`	A Dimensionality Reduction Approach for Convolutional Neural Networks. CoRR Laura Meneghetti, Nicola Demo, Gianluigi Rozza
2021	J	`jnl`	A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems. SIAM J. Sci. Comput. Nicola Demo, Marco Tezzele, Gianluigi Rozza
2021	J	`jnl`	A dynamic mode decomposition extension for the forecasting of parametric dynamical systems. CoRR Francesco Andreuzzi, Nicola Demo, Gianluigi Rozza
2021	J	`jnl`	An extended physics informed neural network for preliminary analysis of parametric optimal control problems. CoRR Nicola Demo, Maria Strazzullo, Gianluigi Rozza
2021	J	`jnl`	Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing. CoRR Nicola Demo, Marco Tezzele, Andrea Mola, Gianluigi Rozza
2021	J	`jnl`	PyGeM: Python Geometrical Morphing. Softw. Impacts Marco Tezzele, Nicola Demo, Andrea Mola, Gianluigi Rozza
2021	J	`jnl`	The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations. CoRR Davide Papapicco, Nicola Demo, Michele Girfoglio, Giovanni Stabile, Gianluigi Rozza
2020	J	`jnl`	A supervised learning approach involving active subspaces for an efficient genetic algorithm in high-dimensional optimization problems. CoRR Nicola Demo, Marco Tezzele, Gianluigi Rozza
2020	J	`jnl`	An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques. CoRR Nicola Demo, Giulio Ortali, Gianluca Gustin, Gianluigi Rozza, Gianpiero Lavini
2020	J	`jnl`	Enhancing CFD predictions in shape design problems by model and parameter space reduction. Adv. Model. Simul. Eng. Sci. Marco Tezzele, Nicola Demo, Giovanni Stabile, Andrea Mola, Gianluigi Rozza
2020	J	`jnl`	Enhancing CFD predictions in shape design problems by model and parameter space reduction. CoRR Marco Tezzele, Nicola Demo, Giovanni Stabile, Andrea Mola, Gianluigi Rozza
2020	J	`jnl`	Gaussian process approach within a data-driven POD framework for fluid dynamics engineering problems. CoRR Giulio Ortali, Nicola Demo, Gianluigi Rozza
2019	J	`jnl`	A non-intrusive approach for proper orthogonal decomposition modal coefficients reconstruction through active subspaces. CoRR Nicola Demo, Marco Tezzele, Gianluigi Rozza
2018	J	`jnl`	EZyRB: Easy Reduced Basis method. J. Open Source Softw. Nicola Demo, Marco Tezzele, Gianluigi Rozza
2018	J	`jnl`	PyDMD: Python Dynamic Mode Decomposition. J. Open Source Softw. Nicola Demo, Marco Tezzele, Gianluigi Rozza
2015	—	`conf`	Experience on Vectorizing Lattice Boltzmann Kernels for Multi- and Many-Core Architectures. PPAM (1) Enrico Calore, Nicola Demo, Sebastiano Fabio Schifano, Raffaele Tripiccione