Marco Tezzele - RankMe

33 papers Journal 33

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Adaptive digital twins for predictive decision-making: Online Bayesian learning of transition dynamics. CoRR Eugenio Varetti, Matteo Torzoni, Marco Tezzele, Andrea Manzoni
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
2024	J	`jnl`	A Local Approach to Parameter Space Reduction for Regression and Classification Tasks. J. Sci. Comput. Francesco Romor, Marco Tezzele, Gianluigi Rozza
2024	J	`jnl`	Adaptive planning for risk-aware predictive digital twins. CoRR Marco Tezzele, Steven Carr, Ufuk Topcu, Karen E. Willcox
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`	Data-driven parameterization refinement for the structural optimization of cruise ship hulls. CoRR Lorenzo Fabris, Marco Tezzele, Ciro Busiello, Mauro Sicchiero, 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 digital twin framework for civil engineering structures. CoRR Matteo Torzoni, Marco Tezzele, Stefano Mariani, Andrea Manzoni, Karen E. Willcox
2022	J	`jnl`	A multi-fidelity approach coupling parameter space reduction and non-intrusive POD with application to structural optimization of passenger ship hulls. CoRR Marco Tezzele, Lorenzo Fabris, Matteo Sidari, Mauro Sicchiero, 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 data-driven partitioned approach for the resolution of time-dependent optimal control problems with dynamic mode decomposition. CoRR Eleonora Donadini, Maria Strazzullo, Marco Tezzele, Gianluigi Rozza
2021	J	`jnl`	A local approach to parameter space reduction for regression and classification tasks. CoRR Francesco Romor, Marco Tezzele, Gianluigi Rozza
2021	J	`jnl`	ATHENA: Advanced Techniques for High Dimensional Parameter Spaces to Enhance Numerical Analysis. CoRR Francesco Romor, Marco Tezzele, Gianluigi Rozza
2021	J	`jnl`	ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis. Softw. Impacts Francesco Romor, Marco Tezzele, 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`	Multi-fidelity data fusion through parameter space reduction with applications to automotive engineering. CoRR Francesco Romor, Marco Tezzele, Markus Mrosek, Carsten Othmer, Gianluigi Rozza
2021	J	`jnl`	PyGeM: Python Geometrical Morphing. Softw. Impacts Marco Tezzele, Nicola Demo, Andrea Mola, 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`	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`	Kernel-based Active Subspaces with application to CFD parametric problems using Discontinuous Galerkin method. CoRR Francesco Romor, Marco Tezzele, Andrea Lario, Gianluigi Rozza
2020	J	`jnl`	Multi-fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces. CoRR Francesco Romor, Marco Tezzele, Gianluigi Rozza
2020	J	`jnl`	On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis. CoRR Mahmoud Gadalla, Marta Cianferra, Marco Tezzele, Giovanni Stabile, Andrea Mola, 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
2019	J	`jnl`	Basic Ideas and Tools for Projection-Based Model Reduction of Parametric Partial Differential Equations. CoRR Gianluigi Rozza, Martin W. Hess, Giovanni Stabile, Marco Tezzele, Francesco Ballarin
2019	J	`jnl`	BladeX: Python Blade Morphing. J. Open Source Softw. Mahmoud Gadalla, Marco Tezzele, Andrea Mola, Gianluigi Rozza
2019	J	`jnl`	Efficient Reduction in Shape Parameter Space Dimension for Ship Propeller Blade Design. CoRR Andrea Mola, Marco Tezzele, Mahmoud Gadalla, Federica Valdenazzi, Davide Grassi, Roberta Padovan, Gianluigi Rozza
2018	J	`jnl`	Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems. Adv. Model. Simul. Eng. Sci. Marco Tezzele, Filippo Salmoiraghi, Andrea Mola, 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