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Paolo Conti
Paolo Conti
The Alan Turing Institute
E-mail confirmado em turing.ac.uk - Página inicial
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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
1162022
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
582023
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
532023
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
152024
EKF–SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics
L Rosafalco, P Conti, A Manzoni, S Mariani, A Frangi
Computer Methods in Applied Mechanics and Engineering 431, 117264, 2024
72024
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
62024
Online learning in bifurcating dynamic systems via SINDy and Kalman filtering
L Rosafalco, P Conti, A Manzoni, S Mariani, A Frangi
arXiv preprint arXiv:2411.04842, 2024
2024
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