| A low-rank projector-splitting integrator for the Vlasov–Maxwell equations with divergence correction L Einkemmer, A Ostermann, C Piazzola Journal of Computational Physics 403, 109063, 2020 | 45 | 2020 |
| Numerical low-rank approximation of matrix differential equations H Mena, A Ostermann, LM Pfurtscheller, C Piazzola Journal of Computational and Applied Mathematics 340, 602-614, 2018 | 42 | 2018 |
| A note on tools for prediction under uncertainty and identifiability of SIR-like dynamical systems for epidemiology C Piazzola, L Tamellini, R Tempone Mathematical Biosciences 332, 108514, 2021 | 29 | 2021 |
| Convergence of a low-rank Lie--Trotter splitting for stiff matrix differential equations A Ostermann, C Piazzola, H Walach SIAM Journal on Numerical Analysis 57 (4), 1947-1966, 2019 | 28 | 2019 |
| Algorithm 1040: The Sparse Grids Matlab Kit-a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification. C Piazzola, L Tamellini ACM Trans. Math. Softw. 50 (1), 7:1-7:22, 2024 | 26* | 2024 |
| Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance C Piazzola, L Tamellini, R Pellegrini, R Broglia, A Serani, M Diez Engineering with Computers 39 (3), 2209-2237, 2023 | 19 | 2023 |
| A splitting approach for the magnetic Schrödinger equation M Caliari, A Ostermann, C Piazzola Journal of Computational and Applied Mathematics 316, 74-85, 2017 | 17 | 2017 |
| Uncertainty quantification of ship resistance via multi-index stochastic collocation and radial basis function surrogates: A comparison C Piazzola, L Tamellini, R Pellegrini, R Broglia, A Serani, M Diez AIAA Aviation 2020 Forum, 3160, 2020 | 15 | 2020 |
| Sparse-grids uncertainty quantification of part-scale additive manufacturing processes M Chiappetta, C Piazzola, M Carraturo, L Tamellini, A Reali, F Auricchio International Journal of Mechanical Sciences 256, 108476, 2023 | 6 | 2023 |
| Inverse and forward sparse-grids-based uncertainty quantification analysis of laser-based powder bed fusion of metals M Chiappetta, C Piazzola, M Carraturo, L Tamellini, A Reali, F Auricchio Int J Mech Sci 256, 108476, 2023 | 1 | 2023 |
| Input-output reduced order modeling for public health intervention evaluation A Viguerie, C Piazzola, MH Islam, EU Jacobson arXiv preprint arXiv:2406.01657, 2024 | | 2024 |
| Uncertainty quantification analysis of bifurcations of the Allen--Cahn equation with random coefficients C Kuehn, C Piazzola, E Ullmann arXiv preprint arXiv:2404.04639, 2024 | | 2024 |
| Data‐informed uncertainty quantification for laser‐based powder bed fusion additive manufacturing M Chiappetta, C Piazzola, L Tamellini, A Reali, F Auricchio, M Carraturo International Journal for Numerical Methods in Engineering, e7542, 2023 | | 2023 |
| Surrogate-based Bayesian characterization of porous and deformable aquifer systems in water stressed regions Y Li, C Zoccarato, L Tamellini, C Piazzola, P Ezquerro, G Bru, ... EGU General Assembly Conference Abstracts, EGU-8761, 2023 | | 2023 |
| Surrogate-based Bayesian characterization of porous and deformable aquifer systems in water stressed regions L Yueting, C Zoccarato, L Tamellini, C Piazzola, P Ezquerro, G Bru, ... EGU General Assembly 2023, 2023 | | 2023 |
| Uncertainty quantification and identifiability of SIR-like dynamical systems C Piazzola | | 2022 |
| Dynamical low-rank approaches for differential equations C Piazzola University of Innsbruck, 2019 | | 2019 |
| A splitting approach for the KP and the magnetic Schrödinger equation A Ostermann, M Caliari, C Piazzola | | |
| MS06-Enabling technologies for uncertainty quantification and opti-mization in real-world applications C Piazzola, R Pellegrini Local organizing committee, 50, 0 | | |
Lorenzo TamelliniCNR-IMATI在 imati.cnr.it 的电子邮件经过验证
