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Andrea ManzoniPolitecnico di Milano在 polimi.it 的电子邮件经过验证
Mengwu GuoCentre for Mathematical Sciences, Lund University在 math.lu.se 的电子邮件经过验证
Jan S HesthavenProfessor of Mathematics and Provost, Ecole Polytechnique Federale de Lausanne (EPFL)在 epfl.ch 的电子邮件经过验证
Attilio FrangiProfessor of Solid and Structural Mechanics, Politecnico di Milano在 polimi.it 的电子邮件经过验证
Maurice AmendtResearch scientist, Amazon在 amazon.lu 的电子邮件经过验证
Giorgio GobatPolitecnico di Milano在 polimi.it 的电子邮件经过验证
Stefania FrescaMOX - Dipartimento di Matematica, Politecnico di Milano在 polimi.it 的电子邮件经过验证
Steven L. BruntonProfessor, University of Washington在 uw.edu 的电子邮件经过验证
J. Nathan KutzProfessor of Applied Mathematics & Electrical and Computer Engineering在 uw.edu 的电子邮件经过验证
Luca RosafalcoPolitecnico di Milano在 polimi.it 的电子邮件经过验证
Jonas KneiflResearch Associate at University of Stuttgart Institute of Engineering and Computational Mechanics在 itm.uni-stuttgart.de 的电子邮件经过验证

Paolo Conti

在 polimi.it 的电子邮件经过验证 - 首页


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Multi-fidelity regression using artificial neural networks: Efficient approximation of parameter-dependent output quantities M Guo, A Manzoni, M Amendt, P Conti, JS Hesthaven Computer methods in applied mechanics and engineering 389, 114378, 2022	79	2022
Multi-fidelity surrogate modeling using long short-term memory networks P Conti, M Guo, A Manzoni, JS Hesthaven Computer methods in applied mechanics and engineering 404, 115811, 2023	33	2023
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions P Conti, G Gobat, S Fresca, A Manzoni, A Frangi Computer Methods in Applied Mechanics and Engineering 411, 116072, 2023	25	2023
Multi-fidelity reduced-order surrogate modelling P Conti, M Guo, A Manzoni, A Frangi, SL Brunton, J Nathan Kutz Proceedings of the Royal Society A 480 (2283), 20230655, 2024	5	2024
EKF-SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics L Rosafalco, P Conti, A Manzoni, S Mariani, A Frangi arXiv preprint arXiv:2404.07536, 2024	1	2024
VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification P Conti, J Kneifl, A Manzoni, A Frangi, J Fehr, SL Brunton, JN Kutz arXiv preprint arXiv:2405.20905, 2024		2024

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