Andrea Manzoni

92 papers C 1Misc 1Journal 89Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Active digital twins via active inference. Eng. Appl. Artif. Intell. Matteo Torzoni, Domenico Maisto, Andrea Manzoni, Francesco Donnarumma, Giovanni Pezzulo, Alberto Corigliano
2026	J	`jnl`	Deep orthogonal decomposition: a continuously adaptive neural network approach to model order reduction of parametrized partial differential equations. Adv. Comput. Math. Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven
2026	J	`jnl`	MoE-Sieve: Routing-Guided LoRA for Efficient MoE Fine-Tuning. CoRR Andrea Manzoni
2026	J	`jnl`	Neural Markov chain Monte Carlo: Bayesian inversion via normalizing flows and variational autoencoders. CoRR Giacomo Bottacini, Matteo Torzoni, Andrea Manzoni
2026	J	`jnl`	VENI, VINDy, VICI: A generative reduced-order modeling framework with uncertainty quantification. Neural Networks Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
2025	J	`jnl`	Active Digital Twins via Active Inference. CoRR Matteo Torzoni, Domenico Maisto, Andrea Manzoni, Francesco Donnarumma, Giovanni Pezzulo, Alberto Corigliano
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`	Enhancing Bayesian model updating in structural health monitoring via learnable mappings. Eng. Comput. Matteo Torzoni, Andrea Manzoni, Stefano Mariani
2025	J	`jnl`	HypeMARL: Multi-Agent Reinforcement Learning For High-Dimensional, Parametric, and Distributed Systems. CoRR Nicolò Botteghi, Matteo Tomasetto, Urban Fasel, Francesco Braghin, Andrea Manzoni
2025	J	`jnl`	HypeRL: Parameter-Informed Reinforcement Learning for Parametric PDEs. CoRR Nicolò Botteghi, Stefania Fresca, Mengwu Guo, Andrea Manzoni
2025	J	`jnl`	Multi-Fidelity Delayed Acceptance: hierarchical MCMC sampling for Bayesian inverse problems combining multiple solvers through deep neural networks. CoRR Filippo Zacchei, Paolo Conti, Attilio Alberto Frangi, Andrea Manzoni
2025	J	`jnl`	On latent dynamics learning in nonlinear reduced order modeling. Neural Networks Nicola Farenga, Stefania Fresca, Simone Brivio, Andrea Manzoni
2025	J	`jnl`	Progressive multi-fidelity learning for physical system predictions. CoRR Paolo Conti, Mengwu Guo, Attilio Frangi, Andrea Manzoni
2025	J	`jnl`	Reduced Order Modeling with Shallow Recurrent Decoder Networks. CoRR Matteo Tomasetto, Jan P. Williams, Francesco Braghin, Andrea Manzoni, J. Nathan Kutz
2025	J	`jnl`	Robust optimal density control of robotic swarms. Autom. Carlo Sinigaglia, Andrea Manzoni, Francesco Braghin, Spring Berman
2024	J	`jnl`	A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces. J. Sci. Comput. Elena Zappon, Andrea Manzoni, Paola Gervasio, Alfio Quarteroni
2024	J	`jnl`	A non-conforming-in-space numerical framework for realistic cardiac electrophysiological outputs. J. Comput. Phys. Elena Zappon, Andrea Manzoni, Alfio Quarteroni
2024	J	`jnl`	Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction. CoRR Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven
2024	J	`jnl`	EKF-SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics. CoRR Luca Rosafalco, Paolo Conti, Andrea Manzoni, Stefano Mariani, Attilio Frangi
2024	J	`jnl`	Enhancing Bayesian model updating in structural health monitoring via learnable mappings. CoRR Matteo Torzoni, Andrea Manzoni, Stefano Mariani
2024	J	`jnl`	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. Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
2024	J	`jnl`	Handling geometrical variability in nonlinear reduced order modeling through Continuous Geometry-Aware DL-ROMs. CoRR Simone Brivio, Stefania Fresca, Andrea Manzoni
2024	J	`jnl`	Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems. CoRR Florian Wolf, Nicolò Botteghi, Urban Fasel, Andrea Manzoni
2024	J	`jnl`	Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models. CoRR Matteo Tomasetto, Francesco Braghin, Andrea Manzoni
2024	J	`jnl`	On latent dynamics learning in nonlinear reduced order modeling. CoRR Nicola Farenga, Stefania Fresca, Simone Brivio, Andrea Manzoni
2024	J	`jnl`	On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. Adv. Comput. Math. Nicola Rares Franco, Daniel Fraulin, Andrea Manzoni, Paolo Zunino
2024	J	`jnl`	PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. CoRR Simone Brivio, Stefania Fresca, Andrea Manzoni
2024	J	`jnl`	Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models. CoRR Matteo Tomasetto, Andrea Manzoni, Francesco Braghin
2024	J	`jnl`	Recurrent Deep Kernel Learning of Dynamical Systems. CoRR Nicolò Botteghi, Paolo Motta, Andrea Manzoni, Paolo Zunino, Mengwu Guo
2024	J	`jnl`	SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study. CoRR Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni, Mara Tanelli
2024	J	`jnl`	VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification. CoRR Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	A digital twin framework for civil engineering structures. CoRR Matteo Torzoni, Marco Tezzele, Stefano Mariani, Andrea Manzoni, Karen E. Willcox
2023	J	`jnl`	A staggered-in-time and non-conforming-in-space numerical framework for realistic cardiac electrophysiology outputs. CoRR Elena Zappon, Andrea Manzoni, Alfio Quarteroni
2023	C	`conf`	A tissue-aware simulation framework for [18F]FLT spatiotemporal uptake in pancreatic ductal adenocarcinoma. CIBCB Lara Cavinato, Jimin Hong, Stefan Reinhard, Martin Wartenberg, Paolo Zunino, Andrea Manzoni, Francesca Ieva, Kuangyu Shi
2023	J	`jnl`	Approximation bounds for convolutional neural networks in operator learning. Neural Networks Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks. CoRR Nicola Rares Franco, Stefania Fresca, Filippo Tombari, Andrea Manzoni
2023	J	`jnl`	Efficient and certified solution of parametrized one-way coupled problems through DEIM-based data projection across non-conforming interfaces. Adv. Comput. Math. Elena Zappon, Andrea Manzoni, Alfio Quarteroni
2023	J	`jnl`	Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. CoRR Simone Brivio, Stefania Fresca, Nicola Rares Franco, Andrea Manzoni
2023	J	`jnl`	Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces. J. Sci. Comput. Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Multi-fidelity reduced-order surrogate modeling. CoRR Paolo Conti, Mengwu Guo, Andrea Manzoni, Attilio Frangi, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	Nonlinear model order reduction for problems with microstructure using mesh informed neural networks. CoRR Piermario Vitullo, Alessio Colombo, Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. CoRR Nicola Rares Franco, Daniel Fraulin, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. Sensors Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2023	J	`jnl`	Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. Comput. Math. Appl. Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino
2023	J	`jnl`	Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. CoRR Ludovica Cicci, Stefania Fresca, Mengwu Guo, Andrea Manzoni, Paolo Zunino
2022	J	`jnl`	A deep learning approach to Reduced Order Modelling of parameter dependent partial differential equations. Math. Comput. Nicola R. Franco, Andrea Manzoni, Paolo Zunino
2022	J	`jnl`	A reduced order model for domain decompositions with non-conforming interfaces. CoRR Elena Zappon, Andrea Manzoni, Paola Gervasio, Alfio Quarteroni
2022	J	`jnl`	Approximation bounds for convolutional neural networks in operator learning. CoRR Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino
2022	J	`jnl`	Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs. J. Sci. Comput. Ludovica Cicci, Stefania Fresca, Andrea Manzoni
2022	J	`jnl`	Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs. CoRR Ludovica Cicci, Stefania Fresca, Andrea Manzoni
2022	J	`jnl`	Density Control of Large-Scale Particles Swarm Through PDE-Constrained Optimization. IEEE Trans. Robotics Carlo Sinigaglia, Andrea Manzoni, Francesco Braghin
2022	J	`jnl`	Efficient and certified solution of parametrized one-way coupled problems through DEIM-based data projection across non-conforming interfaces. CoRR Elena Zappon, Andrea Manzoni, Alfio Quarteroni
2022	J	`jnl`	Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. CoRR Ludovica Cicci, Stefania Fresca, Andrea Manzoni, Alfio Quarteroni
2022	J	`jnl`	Learning Operators with Mesh-Informed Neural Networks. CoRR Nicola Rares Franco, Andrea Manzoni, Paolo Zunino
2022	J	`jnl`	Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. CoRR Federico Fatone, Stefania Fresca, Andrea Manzoni
2022	J	`jnl`	Multi-fidelity surrogate modeling using long short-term memory networks. CoRR Paolo Conti, Mengwu Guo, Andrea Manzoni, Jan S. Hesthaven
2022	J	`jnl`	Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions. CoRR Paolo Conti, Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2022	J	`jnl`	Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. CoRR Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2021	J	`jnl`	A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs. J. Sci. Comput. Stefania Fresca, Luca Dedè, Andrea Manzoni
2021	J	`jnl`	A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations. CoRR Nicola R. Franco, Andrea Manzoni, Paolo Zunino
2021	J	`jnl`	An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics. Sensors Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
2021	J	`jnl`	Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures. CoRR Stefania Fresca, Giorgio Gobat, Patrick Fedeli, Attilio Frangi, Andrea Manzoni
2021	J	`jnl`	Learning High-Order Interactions via Targeted Pattern Search. CoRR Michela Carlotta Massi, Nicola R. Franco, Francesca Ieva, Andrea Manzoni, Anna Maria Paganoni, Paolo Zunino
2021	J	`jnl`	Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities. CoRR Mengwu Guo, Andrea Manzoni, Maurice Amendt, Paolo Conti, Jan S. Hesthaven
2021	J	`jnl`	Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. Comput. Math. Appl. Matteo Salvador, Luca Dedè, Andrea Manzoni
2021	J	`jnl`	Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. CoRR Matteo Salvador, Luca Dedè, Andrea Manzoni
2021	J	`jnl`	Online structural health monitoring by model order reduction and deep learning algorithms. CoRR Luca Rosafalco, Matteo Torzoni, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
2021	J	`jnl`	POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. CoRR Stefania Fresca, Andrea Manzoni
2021	J	`jnl`	Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. CoRR Stefania Fresca, Andrea Manzoni
2021	J	`jnl`	Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. CoRR Giorgio Gobat, Andrea Opreni, Stefania Fresca, Andrea Manzoni, Attilio Frangi
2021	J	`jnl`	SUIHTER: A new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy. CoRR Nicola Parolini, Luca Dedè, Paola F. Antonietti, Giovanni Ardenghi, Andrea Manzoni, Edie Miglio, Andrea Pugliese, Marco Verani, Alfio Quarteroni
2020	J	`jnl`	A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs. CoRR Stefania Fresca, Luca Dedè, Andrea Manzoni
2020	J	`jnl`	Deep learning-based reduced order models in cardiac electrophysiology. CoRR Stefania Fresca, Andrea Manzoni, Luca Dedè, Alfio Quarteroni
2020	J	`jnl`	Fully convolutional networks for structural health monitoring through multivariate time series classification. Adv. Model. Simul. Eng. Sci. Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
2020	J	`jnl`	Fully convolutional networks for structural health monitoring through multivariate time series classification. CoRR Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano
2019	J	`jnl`	Hyper-reduced order models for parametrized unsteady Navier-Stokes equations on domains with variable shape. Adv. Comput. Math. Niccolò Dal Santo, Andrea Manzoni
2019	J	`jnl`	Multi space reduced basis preconditioners for parametrized Stokes equations. Comput. Math. Appl. Niccolò Dal Santo, Simone Deparis, Andrea Manzoni, Alfio Quarteroni
2019	J	`jnl`	Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. CoRR Stefano Pagani, Andrea Manzoni, Kevin Carlberg
2018	J	`jnl`	Multi Space Reduced Basis Preconditioners for Large-Scale Parametrized PDEs. SIAM J. Sci. Comput. Niccolò Dal Santo, Simone Deparis, Andrea Manzoni, Alfio Quarteroni
2017	J	`jnl`	Efficient State/Parameter Estimation in Nonlinear Unsteady PDEs by a Reduced Basis Ensemble Kalman Filter. SIAM/ASA J. Uncertain. Quantification Stefano Pagani, Andrea Manzoni, Alfio Quarteroni
2017	J	`jnl`	The cardiovascular system: Mathematical modelling, numerical algorithms and clinical applications. Acta Numer. Alfio Quarteroni, Andrea Manzoni, Christian Vergara
2016	J	`jnl`	Accurate Solution of Bayesian Inverse Uncertainty Quantification Problems Combining Reduced Basis Methods and Reduction Error Models. SIAM/ASA J. Uncertain. Quantification Andrea Manzoni, Stefano Pagani, Toni Lassila
2016	J	`jnl`	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. Francesco Ballarin, Elena Faggiano, Sonia Ippolito, Andrea Manzoni, Alfio Quarteroni, Gianluigi Rozza, Roberto Scrofani
2016	J	`jnl`	Use of Operational Microwave Link Measurements for the Tomographic Reconstruction of 2-D Maps of Accumulated Rainfall. IEEE Geosci. Remote. Sens. Lett. Michele d'Amico, Andrea Manzoni, Gian Leonardo Solazzi
2015	J	`jnl`	Efficient model reduction of parametrized systems by matrix discrete empirical interpolation. J. Comput. Phys. Federico Negri, Andrea Manzoni, David Amsallem
2015	J	`jnl`	Heuristic strategies for the approximation of stability factors in quadratically nonlinear parametrized PDEs. Adv. Comput. Math. Andrea Manzoni, Federico Negri
2015	J	`jnl`	Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations. Comput. Math. Appl. Federico Negri, Andrea Manzoni, Gianluigi Rozza
2014	J	`jnl`	Shape Optimization by Free-Form Deformation: Existence Results and Numerical Solution for Stokes Flows. J. Sci. Comput. Francesco Ballarin, Andrea Manzoni, Gianluigi Rozza, Sandro Salsa
2013	J	`jnl`	Reduced Basis Method for Parametrized Elliptic Optimal Control Problems. SIAM J. Sci. Comput. Federico Negri, Gianluigi Rozza, Andrea Manzoni, Alfio Quarteroni
2013	J	`jnl`	Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants. Numerische Mathematik Gianluigi Rozza, Dinh Bao Phuong Huynh, Andrea Manzoni
2012	Misc	`conf`	A Reduced-Order Strategy for Solving Inverse Bayesian Shape Identification Problems in Physiological Flows. HPSC Andrea Manzoni, Toni Lassila, Alfio Quarteroni, Gianluigi Rozza
2011	—	`conf`	Reduction Strategies for Shape Dependent Inverse Problems in Haemodynamics. System Modelling and Optimization Toni Lassila, Andrea Manzoni, Gianluigi Rozza