Reduction Strategies for Shape Dependent Inverse Problems in Haemodynamics. - Toni Lassila; Andrea Manzoni; Gianluigi Rozza (System Modelling and Optimization, 2011)

A Reduced-Order Strategy for Solving Inverse Bayesian Shape Identification Problems in Physiological Flows. - Andrea Manzoni; Toni Lassila; Alfio Quarteroni; Gianluigi Rozza (HPSC, 2012)

Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants. - Gianluigi Rozza; Dinh Bao Phuong Huynh; Andrea Manzoni (Numerische Mathematik, 2013)

Reduced Basis Method for Parametrized Elliptic Optimal Control Problems. - Federico Negri; Gianluigi Rozza; Andrea Manzoni; Alfio Quarteroni (SIAM J. Sci. Comput., 2013)

Shape Optimization by Free-Form Deformation: Existence Results and Numerical Solution for Stokes Flows. - Francesco Ballarin; Andrea Manzoni; Gianluigi Rozza; Sandro Salsa (J. Sci. Comput., 2014)

Heuristic strategies for the approximation of stability factors in quadratically nonlinear parametrized PDEs. - Andrea Manzoni; Federico Negri (Adv. Comput. Math., 2015)

Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations. - Federico Negri; Andrea Manzoni; Gianluigi Rozza (Comput. Math. Appl., 2015)

Efficient model reduction of parametrized systems by matrix discrete empirical interpolation. - Federico Negri; Andrea Manzoni; David Amsallem (J. Comput. Phys., 2015)

Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization. - Francesco Ballarin; Elena Faggiano; Sonia Ippolito; Andrea Manzoni; Alfio Quarteroni; Gianluigi Rozza; Roberto Scrofani (J. Comput. Phys., 2016)

Accurate Solution of Bayesian Inverse Uncertainty Quantification Problems Combining Reduced Basis Methods and Reduction Error Models. - Andrea Manzoni; Stefano Pagani; Toni Lassila (SIAM/ASA J. Uncertain. Quantification, 2016)

Use of Operational Microwave Link Measurements for the Tomographic Reconstruction of 2-D Maps of Accumulated Rainfall. - Michele d'Amico; Andrea Manzoni; Gian Leonardo Solazzi (IEEE Geosci. Remote. Sens. Lett., 2016)

The cardiovascular system: Mathematical modelling, numerical algorithms and clinical applications. - Alfio Quarteroni; Andrea Manzoni; Christian Vergara (Acta Numer., 2017)

Efficient State/Parameter Estimation in Nonlinear Unsteady PDEs by a Reduced Basis Ensemble Kalman Filter. - Stefano Pagani; Andrea Manzoni; Alfio Quarteroni (SIAM/ASA J. Uncertain. Quantification, 2017)

Multi Space Reduced Basis Preconditioners for Large-Scale Parametrized PDEs. - Niccolò Dal Santo; Simone Deparis; Andrea Manzoni; Alfio Quarteroni (SIAM J. Sci. Comput., 2018)

Hyper-reduced order models for parametrized unsteady Navier-Stokes equations on domains with variable shape. - Niccolò Dal Santo; Andrea Manzoni (Adv. Comput. Math., 2019)

Multi space reduced basis preconditioners for parametrized Stokes equations. - Niccolò Dal Santo; Simone Deparis; Andrea Manzoni; Alfio Quarteroni (Comput. Math. Appl., 2019)

Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. - Stefano Pagani; Andrea Manzoni; Kevin Carlberg (CoRR, 2019)

Fully convolutional networks for structural health monitoring through multivariate time series classification. - Luca Rosafalco; Andrea Manzoni; Stefano Mariani 002; Alberto Corigliano (Adv. Model. Simul. Eng. Sci., 2020)

Deep learning-based reduced order models in cardiac electrophysiology. - Stefania Fresca; Andrea Manzoni; Luca Dedè; Alfio Quarteroni (CoRR, 2020)

Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. - Matteo Salvador; Luca Dedè; Andrea Manzoni (Comput. Math. Appl., 2021)

SUIHTER: A new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy. - Nicola Parolini; Luca Dedè; Paola F. Antonietti; Giovanni Ardenghi; Andrea Manzoni; Edie Miglio; Andrea Pugliese 003; Marco Verani; Alfio Quarteroni (CoRR, 2021)

POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. - Stefania Fresca; Andrea Manzoni (CoRR, 2021)

Learning High-Order Interactions via Targeted Pattern Search. - Michela Carlotta Massi; Nicola R. Franco; Francesca Ieva; Andrea Manzoni; Anna Maria Paganoni; Paolo Zunino (CoRR, 2021)

Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities. - Mengwu Guo; Andrea Manzoni; Maurice Amendt; Paolo Conti; Jan S. Hesthaven (CoRR, 2021)

Online structural health monitoring by model order reduction and deep learning algorithms. - Luca Rosafalco; Matteo Torzoni; Andrea Manzoni; Stefano Mariani 002; Alberto Corigliano (CoRR, 2021)

Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. - Stefania Fresca; Andrea Manzoni (CoRR, 2021)

Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. - Giorgio Gobat; Andrea Opreni; Stefania Fresca; Andrea Manzoni; Attilio Frangi (CoRR, 2021)

Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures. - Stefania Fresca; Giorgio Gobat; Patrick Fedeli; Attilio Frangi; Andrea Manzoni (CoRR, 2021)

A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs. - Stefania Fresca; Luca Dedè; Andrea Manzoni (J. Sci. Comput., 2021)

An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics. - Luca Rosafalco; Andrea Manzoni; Stefano Mariani 002; Alberto Corigliano (Sensors, 2021)

Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. - Federico Fatone; Stefania Fresca; Andrea Manzoni (CoRR, 2022)

Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. - Ludovica Cicci; Stefania Fresca; Andrea Manzoni; Alfio Quarteroni (CoRR, 2022)

Learning Operators with Mesh-Informed Neural Networks. - Nicola Rares Franco; Andrea Manzoni; Paolo Zunino (CoRR, 2022)

Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. - Giorgio Gobat; Stefania Fresca; Andrea Manzoni; Attilio Frangi (CoRR, 2022)

Multi-fidelity surrogate modeling using long short-term memory networks. - Paolo Conti; Mengwu Guo; Andrea Manzoni; Jan S. Hesthaven (CoRR, 2022)

Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions. - Paolo Conti; Giorgio Gobat; Stefania Fresca; Andrea Manzoni; Attilio Frangi (CoRR, 2022)

Deep-HyROMnet: A Deep Learning-Based Operator Approximation for Hyper-Reduction of Nonlinear Parametrized PDEs. - Ludovica Cicci; Stefania Fresca; Andrea Manzoni (J. Sci. Comput., 2022)

Density Control of Large-Scale Particles Swarm Through PDE-Constrained Optimization. - Carlo Sinigaglia; Andrea Manzoni; Francesco Braghin (IEEE Trans. Robotics, 2022)

A deep learning approach to Reduced Order Modelling of parameter dependent partial differential equations. - Nicola R. Franco; Andrea Manzoni; Paolo Zunino (Math. Comput., 2022)

A tissue-aware simulation framework for [18F]FLT spatiotemporal uptake in pancreatic ductal adenocarcinoma. - Lara Cavinato; Jimin Hong; Stefan Reinhard; Martin Wartenberg; Paolo Zunino; Andrea Manzoni; Francesca Ieva; Kuangyu Shi (CIBCB, 2023)

A digital twin framework for civil engineering structures. - Matteo Torzoni; Marco Tezzele; Stefano Mariani 002; Andrea Manzoni; Karen E. Willcox (CoRR, 2023)

Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks. - Nicola Rares Franco; Stefania Fresca; Filippo Tombari; Andrea Manzoni (CoRR, 2023)

A staggered-in-time and non-conforming-in-space numerical framework for realistic cardiac electrophysiology outputs. - Elena Zappon; Andrea Manzoni; Alfio Quarteroni (CoRR, 2023)

Multi-fidelity reduced-order surrogate modeling. - Paolo Conti; Mengwu Guo; Andrea Manzoni; Attilio Frangi; Steven L. Brunton; J. Nathan Kutz (CoRR, 2023)

Nonlinear model order reduction for problems with microstructure using mesh informed neural networks. - Piermario Vitullo; Alessio Colombo; Nicola Rares Franco; Andrea Manzoni; Paolo Zunino (CoRR, 2023)

Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. - Giorgio Gobat; Stefania Fresca; Andrea Manzoni; Attilio Frangi (Sensors, 2023)

Efficient and certified solution of parametrized one-way coupled problems through DEIM-based data projection across non-conforming interfaces. - Elena Zappon; Andrea Manzoni; Alfio Quarteroni (Adv. Comput. Math., 2023)

Approximation bounds for convolutional neural networks in operator learning. - Nicola Rares Franco; Stefania Fresca; Andrea Manzoni; Paolo Zunino (Neural Networks, 2023)

Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression. - Ludovica Cicci; Stefania Fresca; Mengwu Guo; Andrea Manzoni; Paolo Zunino (Comput. Math. Appl., 2023)

Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces. - Nicola Rares Franco; Andrea Manzoni; Paolo Zunino (J. Sci. Comput., 2023)

SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study. - Aurelio Raffa Ugolini; Valentina Breschi; Andrea Manzoni; Mara Tanelli (CoRR, 2024)

EKF-SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics. - Luca Rosafalco; Paolo Conti; Andrea Manzoni; Stefano Mariani 002; Attilio Frangi (CoRR, 2024)

Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction. - Nicola Rares Franco; Andrea Manzoni; Paolo Zunino; Jan S. Hesthaven (CoRR, 2024)

PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. - Simone Brivio; Stefania Fresca; Andrea Manzoni (CoRR, 2024)

Enhancing Bayesian model updating in structural health monitoring via learnable mappings. - Matteo Torzoni; Andrea Manzoni; Stefano Mariani 002 (CoRR, 2024)

Recurrent Deep Kernel Learning of Dynamical Systems. - Nicolò Botteghi; Paolo Motta; Andrea Manzoni; Paolo Zunino; Mengwu Guo (CoRR, 2024)

VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification. - Paolo Conti; Jonas Kneifl; Andrea Manzoni; Attilio Frangi; Jörg Fehr; Steven L. Brunton; J. Nathan Kutz (CoRR, 2024)

Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models. - Matteo Tomasetto; Andrea Manzoni; Francesco Braghin (CoRR, 2024)

Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems. - Florian Wolf 006; Nicolò Botteghi; Urban Fasel; Andrea Manzoni (CoRR, 2024)

Handling geometrical variability in nonlinear reduced order modeling through Continuous Geometry-Aware DL-ROMs. - Simone Brivio; Stefania Fresca; Andrea Manzoni (CoRR, 2024)

Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models. - Matteo Tomasetto; Francesco Braghin; Andrea Manzoni (CoRR, 2024)

A non-conforming-in-space numerical framework for realistic cardiac electrophysiological outputs. - Elena Zappon; Andrea Manzoni; Alfio Quarteroni (J. Comput. Phys., 2024)

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces. - Elena Zappon; Andrea Manzoni; Paola Gervasio; Alfio Quarteroni (J. Sci. Comput., 2024)

Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition. - Simone Brivio; Stefania Fresca; Nicola Rares Franco; Andrea Manzoni (Adv. Comput. Math., 2024)

On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields. - Nicola Rares Franco; Daniel Fraulin; Andrea Manzoni; Paolo Zunino (Adv. Comput. Math., 2024)

Robust optimal density control of robotic swarms. - Carlo Sinigaglia; Andrea Manzoni; Francesco Braghin; Spring Berman (Autom., 2025)

On latent dynamics learning in nonlinear reduced order modeling. - Nicola Farenga; Stefania Fresca; Simone Brivio; Andrea Manzoni (Neural Networks, 2025)

HypeRL: Parameter-Informed Reinforcement Learning for Parametric PDEs. - Nicolò Botteghi; Stefania Fresca; Mengwu Guo; Andrea Manzoni (CoRR, 2025)

Reduced Order Modeling with Shallow Recurrent Decoder Networks. - Matteo Tomasetto; Jan P. Williams; Francesco Braghin; Andrea Manzoni; J. Nathan Kutz (CoRR, 2025)

Active Digital Twins via Active Inference. - Matteo Torzoni; Domenico Maisto; Andrea Manzoni; Francesco Donnarumma; Giovanni Pezzulo; Alberto Corigliano (CoRR, 2025)