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Andrea Manzoni
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2020 – today
- 2024
- [j30]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): 33 (2024) - [j29]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): 96 (2024) - [j28]Elena Zappon, Andrea Manzoni, Alfio Quarteroni:
A non-conforming-in-space numerical framework for realistic cardiac electrophysiological outputs. J. Comput. Phys. 502: 112815 (2024) - [j27]Elena Zappon, Andrea Manzoni, Paola Gervasio, Alfio Quarteroni:
A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces. J. Sci. Comput. 99(1): 22 (2024) - [i41]Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni, Mara Tanelli:
SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study. CoRR abs/2403.00578 (2024) - [i40]Luca Rosafalco, Paolo Conti, Andrea Manzoni, Stefano Mariani, Attilio Frangi:
EKF-SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics. CoRR abs/2404.07536 (2024) - [i39]Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven:
Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction. CoRR abs/2404.18841 (2024) - [i38]Simone Brivio, Stefania Fresca, Andrea Manzoni:
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs. CoRR abs/2405.08558 (2024) - [i37]Matteo Torzoni, Andrea Manzoni, Stefano Mariani:
Enhancing Bayesian model updating in structural health monitoring via learnable mappings. CoRR abs/2405.13648 (2024) - [i36]Nicolò Botteghi, Paolo Motta, Andrea Manzoni, Paolo Zunino, Mengwu Guo:
Recurrent Deep Kernel Learning of Dynamical Systems. CoRR abs/2405.19785 (2024) - [i35]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 abs/2405.20905 (2024) - [i34]Nicola Farenga, Stefania Fresca, Simone Brivio, Andrea Manzoni:
On latent dynamics learning in nonlinear reduced order modeling. CoRR abs/2408.15183 (2024) - [i33]Matteo Tomasetto, Andrea Manzoni, Francesco Braghin:
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models. CoRR abs/2409.05709 (2024) - 2023
- [j26]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): 21 (2023) - [j25]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: 1-23 (2023) - [j24]Nicola Rares Franco, Andrea Manzoni, Paolo Zunino:
Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces. J. Sci. Comput. 97(2): 35 (2023) - [j23]Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino:
Approximation bounds for convolutional neural networks in operator learning. Neural Networks 161: 129-141 (2023) - [j22]Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. Sensors 23(6): 3001 (2023) - [c3]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: 1-9 - [i32]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 abs/2302.08216 (2023) - [i31]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 abs/2305.04680 (2023) - [i30]Matteo Torzoni, Marco Tezzele, Stefano Mariani, Andrea Manzoni, Karen E. Willcox:
A digital twin framework for civil engineering structures. CoRR abs/2308.01445 (2023) - [i29]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 abs/2308.01602 (2023) - [i28]Elena Zappon, Andrea Manzoni, Alfio Quarteroni:
A staggered-in-time and non-conforming-in-space numerical framework for realistic cardiac electrophysiology outputs. CoRR abs/2308.03884 (2023) - [i27]Paolo Conti, Mengwu Guo, Andrea Manzoni, Attilio Frangi, Steven L. Brunton, J. Nathan Kutz:
Multi-fidelity reduced-order surrogate modeling. CoRR abs/2309.00325 (2023) - [i26]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 abs/2309.07815 (2023) - [i25]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 abs/2310.12095 (2023) - 2022
- [j21]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): 57 (2022) - [j20]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): 483-524 (2022) - [j19]Carlo Sinigaglia, Andrea Manzoni, Francesco Braghin:
Density Control of Large-Scale Particles Swarm Through PDE-Constrained Optimization. IEEE Trans. Robotics 38(6): 3530-3549 (2022) - [i24]Federico Fatone, Stefania Fresca, Andrea Manzoni:
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models. CoRR abs/2201.10215 (2022) - [i23]Ludovica Cicci, Stefania Fresca, Andrea Manzoni:
Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs. CoRR abs/2202.02658 (2022) - [i22]Ludovica Cicci, Stefania Fresca, Andrea Manzoni, Alfio Quarteroni:
Efficient approximation of cardiac mechanics through reduced order modeling with deep learning-based operator approximation. CoRR abs/2202.03904 (2022) - [i21]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 abs/2203.09226 (2022) - [i20]Nicola Rares Franco, Andrea Manzoni, Paolo Zunino:
Learning Operators with Mesh-Informed Neural Networks. CoRR abs/2203.11648 (2022) - [i19]Giorgio Gobat, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches. CoRR abs/2205.05928 (2022) - [i18]Elena Zappon, Andrea Manzoni, Paola Gervasio, Alfio Quarteroni:
A reduced order model for domain decompositions with non-conforming interfaces. CoRR abs/2206.09618 (2022) - [i17]Nicola Rares Franco, Stefania Fresca, Andrea Manzoni, Paolo Zunino:
Approximation bounds for convolutional neural networks in operator learning. CoRR abs/2207.01546 (2022) - [i16]Paolo Conti, Mengwu Guo, Andrea Manzoni, Jan S. Hesthaven:
Multi-fidelity surrogate modeling using long short-term memory networks. CoRR abs/2208.03115 (2022) - [i15]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 abs/2211.06786 (2022) - 2021
- [j18]Matteo Salvador, Luca Dedè, Andrea Manzoni:
Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. Comput. Math. Appl. 104: 1-13 (2021) - [j17]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): 61 (2021) - [j16]Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano:
An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics. Sensors 21(12): 4207 (2021) - [i14]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 abs/2101.03369 (2021) - [i13]Stefania Fresca, Andrea Manzoni:
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. CoRR abs/2101.11845 (2021) - [i12]Michela Carlotta Massi, Nicola R. Franco, Francesca Ieva, Andrea Manzoni, Anna Maria Paganoni, Paolo Zunino:
Learning High-Order Interactions via Targeted Pattern Search. CoRR abs/2102.12974 (2021) - [i11]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 abs/2102.13403 (2021) - [i10]Nicola R. Franco, Andrea Manzoni, Paolo Zunino:
A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations. CoRR abs/2103.06183 (2021) - [i9]Luca Rosafalco, Matteo Torzoni, Andrea Manzoni, Stefano Mariani, Alberto Corigliano:
Online structural health monitoring by model order reduction and deep learning algorithms. CoRR abs/2103.14328 (2021) - [i8]Matteo Salvador, Luca Dedè, Andrea Manzoni:
Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks. CoRR abs/2103.17152 (2021) - [i7]Stefania Fresca, Andrea Manzoni:
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models. CoRR abs/2106.05722 (2021) - [i6]Giorgio Gobat, Andrea Opreni, Stefania Fresca, Andrea Manzoni, Attilio Frangi:
Reduced order modeling of nonlinear microstructures through Proper Orthogonal Decomposition. CoRR abs/2109.12184 (2021) - [i5]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 abs/2111.12511 (2021) - 2020
- [j15]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): 38 (2020) - [i4]Stefania Fresca, Luca Dedè, Andrea Manzoni:
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs. CoRR abs/2001.04001 (2020) - [i3]Luca Rosafalco, Andrea Manzoni, Stefano Mariani, Alberto Corigliano:
Fully convolutional networks for structural health monitoring through multivariate time series classification. CoRR abs/2002.07032 (2020) - [i2]Stefania Fresca, Andrea Manzoni, Luca Dedè, Alfio Quarteroni:
Deep learning-based reduced order models in cardiac electrophysiology. CoRR abs/2006.03040 (2020)
2010 – 2019
- 2019
- [j14]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): 2463-2501 (2019) - [j13]Niccolò Dal Santo, Simone Deparis, Andrea Manzoni, Alfio Quarteroni:
Multi space reduced basis preconditioners for parametrized Stokes equations. Comput. Math. Appl. 77(6): 1583-1604 (2019) - [i1]Stefano Pagani, Andrea Manzoni, Kevin Carlberg:
Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. CoRR abs/1901.02792 (2019) - 2018
- [j12]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) - 2017
- [j11]Alfio Quarteroni, Andrea Manzoni, Christian Vergara:
The cardiovascular system: Mathematical modelling, numerical algorithms and clinical applications. Acta Numer. 26: 365-590 (2017) - [j10]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): 890-921 (2017) - 2016
- [j9]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: 609-628 (2016) - [j8]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): 380-412 (2016) - [j7]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): 1827-1831 (2016) - 2015
- [j6]Andrea Manzoni, Federico Negri:
Heuristic strategies for the approximation of stability factors in quadratically nonlinear parametrized PDEs. Adv. Comput. Math. 41(5): 1255-1288 (2015) - [j5]Federico Negri, Andrea Manzoni, Gianluigi Rozza:
Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations. Comput. Math. Appl. 69(4): 319-336 (2015) - [j4]Federico Negri, Andrea Manzoni, David Amsallem:
Efficient model reduction of parametrized systems by matrix discrete empirical interpolation. J. Comput. Phys. 303: 431-454 (2015) - 2014
- [j3]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): 537-563 (2014) - 2013
- [j2]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): 115-152 (2013) - [j1]Federico Negri, Gianluigi Rozza, Andrea Manzoni, Alfio Quarteroni:
Reduced Basis Method for Parametrized Elliptic Optimal Control Problems. SIAM J. Sci. Comput. 35(5) (2013) - 2012
- [c2]Andrea Manzoni, Toni Lassila, Alfio Quarteroni, Gianluigi Rozza:
A Reduced-Order Strategy for Solving Inverse Bayesian Shape Identification Problems in Physiological Flows. HPSC 2012: 145-155 - 2011
- [c1]Toni Lassila, Andrea Manzoni, Gianluigi Rozza:
Reduction Strategies for Shape Dependent Inverse Problems in Haemodynamics. System Modelling and Optimization 2011: 397-406
Coauthor Index
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last updated on 2024-12-10 20:51 CET by the dblp team
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