Andrea Manzoni

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 67

Top Topics

Mathematical Model

Top Venues

Adv. Comput. Math.

J. Sci. Comput.

Comput. Math. Appl.

Publications

Matteo Torzoni, Andrea Manzoni, Stefano Mariani
Enhancing Bayesian model updating in structural health monitoring via learnable mappings. CoRR (2024)
Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification. CoRR (2024)
Luca Rosafalco, Paolo Conti, Andrea Manzoni, Stefano Mariani, Attilio Frangi
EKF-SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics. CoRR (2024)
Nicola Rares Franco, Daniel Fraulin, Andrea Manzoni, Paolo Zunino
On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. Adv. Comput. Math. 50 (5) (2024)
Simone Brivio, Stefania Fresca, Andrea Manzoni
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. CoRR (2024)
Nicolò Botteghi, Paolo Motta, Andrea Manzoni, Paolo Zunino, Mengwu Guo
Recurrent Deep Kernel Learning of Dynamical Systems. CoRR (2024)
Elena Zappon, Andrea Manzoni, Alfio Quarteroni
A non-conforming-in-space numerical framework for realistic cardiac electrophysiological outputs. J. Comput. Phys. 502 (2024)
Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven
Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction. CoRR (2024)
Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni, Mara Tanelli
SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study. CoRR (2024)
Elena Zappon, Andrea Manzoni, Paola Gervasio, Alfio Quarteroni
A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces. J. Sci. Comput. 99 (1) (2024)
Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. Adv. Comput. Math. 50 (3) (2024)
Lara Cavinato, Jimin Hong, Stefan Reinhard, Martin Wartenberg, Paolo Zunino, Andrea Manzoni, Francesca Ieva, Kuangyu Shi
A tissue-aware simulation framework for [18F]FLT spatiotemporal uptake in pancreatic ductal adenocarcinoma. CIBCB (2023)
Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. CoRR (2023)
Nicola Rares Franco, Daniel Fraulin, Andrea Manzoni, Paolo Zunino
On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. CoRR (2023)
Elena Zappon, Andrea Manzoni, Alfio Quarteroni
A staggered-in-time and non-conforming-in-space numerical framework for realistic cardiac electrophysiology outputs. CoRR (2023)
Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces. J. Sci. Comput. 97 (2) (2023)
Paolo Conti, Mengwu Guo, Andrea Manzoni, Attilio Frangi, Steven L. Brunton, J. Nathan Kutz
Multi-fidelity reduced-order surrogate modeling. CoRR (2023)
Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. Sensors 23 (6) (2023)
Elena Zappon, Andrea Manzoni, Alfio Quarteroni
Efficient and certified solution of parametrized one-way coupled problems through DEIM-based data projection across non-conforming interfaces. Adv. Comput. Math. 49 (2) (2023)
Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. Comput. Math. Appl. 149 (2023)
Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
Approximation bounds for convolutional neural networks in operator learning. Neural Networks 161 (2023)
Nicola Rares Franco, Stefania Fresca, Filippo Tombari, Andrea Manzoni
Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks. CoRR (2023)
Matteo Torzoni, Marco Tezzele, Stefano Mariani, Andrea Manzoni, Karen E. Willcox
A digital twin framework for civil engineering structures. CoRR (2023)
Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. CoRR (2023)
Piermario Vitullo, Alessio Colombo, Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
Nonlinear model order reduction for problems with microstructure using mesh informed neural networks. CoRR (2023)
Paolo Conti, Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions. CoRR (2022)
Ludovica Cicci, Stefania Fresca, Andrea Manzoni
Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs. J. Sci. Comput. 93 (2) (2022)
Federico Fatone, Stefania Fresca, Andrea Manzoni
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. CoRR (2022)
Nicola R. Franco, Andrea Manzoni, Paolo Zunino
A deep learning approach to Reduced Order Modelling of parameter dependent partial differential equations. Math. Comput. 92 (340) (2022)
Paolo Conti, Mengwu Guo, Andrea Manzoni, Jan S. Hesthaven
Multi-fidelity surrogate modeling using long short-term memory networks. CoRR (2022)
Ludovica Cicci, Stefania Fresca, Andrea Manzoni
Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs. CoRR (2022)
Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. CoRR (2022)
Ludovica Cicci, Stefania Fresca, Andrea Manzoni, Alfio Quarteroni
Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. CoRR (2022)
Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
Learning Operators with Mesh-Informed Neural Networks. CoRR (2022)
Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
Approximation bounds for convolutional neural networks in operator learning. CoRR (2022)
Elena Zappon, Andrea Manzoni, Paola Gervasio, Alfio Quarteroni
A reduced order model for domain decompositions with non-conforming interfaces. CoRR (2022)
Elena Zappon, Andrea Manzoni, Alfio Quarteroni
Efficient and certified solution of parametrized one-way coupled problems through DEIM-based data projection across non-conforming interfaces. CoRR (2022)
Carlo Sinigaglia, Andrea Manzoni, Francesco Braghin
Density Control of Large-Scale Particles Swarm Through PDE-Constrained Optimization. IEEE Trans. Robotics 38 (6) (2022)
Stefania Fresca, Giorgio Gobat, Patrick Fedeli, Attilio Frangi, Andrea Manzoni
Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures. CoRR (2021)
Nicola Parolini, Luca Dedè, Paola F. Antonietti, Giovanni Ardenghi, Andrea Manzoni, Edie Miglio, Andrea Pugliese, Marco Verani, Alfio Quarteroni
SUIHTER: A new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy. CoRR (2021)
Giorgio Gobat, A. Opreni, Stefania Fresca, Andrea Manzoni, Attilio Frangi
Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. CoRR (2021)
Mengwu Guo, Andrea Manzoni, Maurice Amendt, Paolo Conti, Jan S. Hesthaven
Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities. CoRR (2021)
Stefania Fresca, Luca Dedè, Andrea Manzoni
A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs. J. Sci. Comput. 87 (2) (2021)
Matteo Salvador, Luca Dedè, Andrea Manzoni
Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. CoRR (2021)
Nicola R. Franco, Andrea Manzoni, Paolo Zunino
A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations. CoRR (2021)
Michela Carlotta Massi, Nicola R. Franco, Francesca Ieva, Andrea Manzoni, Anna Maria Paganoni, Paolo Zunino
Learning High-Order Interactions via Targeted Pattern Search. CoRR (2021)
Matteo Salvador, Luca Dedè, Andrea Manzoni
Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. Comput. Math. Appl. 104 (2021)
Luca Rosafalco, Matteo Torzoni, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
Online structural health monitoring by model order reduction and deep learning algorithms. CoRR (2021)
Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics. Sensors 21 (12) (2021)
Stefania Fresca, Andrea Manzoni
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. CoRR (2021)
Stefania Fresca, Andrea Manzoni
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. CoRR (2021)
Stefania Fresca, Andrea Manzoni, Luca Dedè, Alfio Quarteroni
Deep learning-based reduced order models in cardiac electrophysiology. CoRR (2020)
Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
Fully convolutional networks for structural health monitoring through multivariate time series classification. Adv. Model. Simul. Eng. Sci. 7 (1) (2020)
Stefania Fresca, Luca Dedè, Andrea Manzoni
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs. CoRR (2020)
Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
Fully convolutional networks for structural health monitoring through multivariate time series classification. CoRR (2020)
Niccolò Dal Santo, Andrea Manzoni
Hyper-reduced order models for parametrized unsteady Navier-Stokes equations on domains with variable shape. Adv. Comput. Math. 45 (5) (2019)
Niccolò Dal Santo, Simone Deparis, Andrea Manzoni, Alfio Quarteroni
Multi space reduced basis preconditioners for parametrized Stokes equations. Comput. Math. Appl. 77 (6) (2019)
Stefano Pagani, Andrea Manzoni, Kevin Carlberg
Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. CoRR (2019)
Niccolò Dal Santo, Simone Deparis, Andrea Manzoni, Alfio Quarteroni
Multi Space Reduced Basis Preconditioners for Large-Scale Parametrized PDEs. SIAM J. Sci. Comput. 40 (2) (2018)
Stefano Pagani, Andrea Manzoni, Alfio Quarteroni
Efficient State/Parameter Estimation in Nonlinear Unsteady PDEs by a Reduced Basis Ensemble Kalman Filter. SIAM/ASA J. Uncertain. Quantification 5 (1) (2017)
Alfio Quarteroni, Andrea Manzoni, Christian Vergara
The cardiovascular system: Mathematical modelling, numerical algorithms and clinical applications. Acta Numer. 26 (2017)
Andrea Manzoni, Stefano Pagani, Toni Lassila
Accurate Solution of Bayesian Inverse Uncertainty Quantification Problems Combining Reduced Basis Methods and Reduction Error Models. SIAM/ASA J. Uncertain. Quantification 4 (1) (2016)
Francesco Ballarin, Elena Faggiano, Sonia Ippolito, Andrea Manzoni, Alfio Quarteroni, Gianluigi Rozza, Roberto Scrofani
Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization. J. Comput. Phys. 315 (2016)
Michele d'Amico, Andrea Manzoni, Gian Leonardo Solazzi
Use of Operational Microwave Link Measurements for the Tomographic Reconstruction of 2-D Maps of Accumulated Rainfall. IEEE Geosci. Remote. Sens. Lett. 13 (12) (2016)
Federico Negri, Andrea Manzoni, David Amsallem
Efficient model reduction of parametrized systems by matrix discrete empirical interpolation. J. Comput. Phys. 303 (2015)
Federico Negri, Andrea Manzoni, Gianluigi Rozza
Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations. Comput. Math. Appl. 69 (4) (2015)
Andrea Manzoni, Federico Negri
Heuristic strategies for the approximation of stability factors in quadratically nonlinear parametrized PDEs. Adv. Comput. Math. 41 (5) (2015)
Francesco Ballarin, Andrea Manzoni, Gianluigi Rozza, Sandro Salsa
Shape Optimization by Free-Form Deformation: Existence Results and Numerical Solution for Stokes Flows. J. Sci. Comput. 60 (3) (2014)
Gianluigi Rozza, Dinh Bao Phuong Huynh, Andrea Manzoni
Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants. Numerische Mathematik 125 (1) (2013)
Federico Negri, Gianluigi Rozza, Andrea Manzoni, Alfio Quarteroni
Reduced Basis Method for Parametrized Elliptic Optimal Control Problems. SIAM J. Sci. Comput. 35 (5) (2013)
Andrea Manzoni, Toni Lassila, Alfio Quarteroni, Gianluigi Rozza
A Reduced-Order Strategy for Solving Inverse Bayesian Shape Identification Problems in Physiological Flows. HPSC (2012)
Toni Lassila, Andrea Manzoni, Gianluigi Rozza
Reduction Strategies for Shape Dependent Inverse Problems in Haemodynamics. System Modelling and Optimization (2011)