| IR Tools: a MATLAB package of iterative regularization methods and large-scale test problems S Gazzola, PC Hansen, JG Nagy Numerical Algorithms 81 (3), 773-811, 2019 | 227 | 2019 |
| On Krylov projection methods and Tikhonov regularization S Gazzola, P Novati, MR Russo Electron. Trans. Numer. Anal 44 (1), 83-123, 2015 | 124 | 2015 |
| Generalized Arnoldi--Tikhonov Method for Sparse Reconstruction S Gazzola, JG Nagy SIAM Journal on Scientific Computing 36 (2), B225-B247, 2014 | 79 | 2014 |
| Automatic parameter setting for Arnoldi–Tikhonov methods S Gazzola, P Novati Journal of Computational and Applied Mathematics 256, 180-195, 2014 | 44 | 2014 |
| Flexible Krylov Methods for Regularization J Chung, S Gazzola SIAM Journal on Scientific Computing 41 (5), S149-S171, 2019 | 43 | 2019 |
| Fast nonnegative least squares through flexible Krylov subspaces S Gazzola, Y Wiaux SIAM Journal on Scientific Computing 39 (2), A655-A679, 2017 | 39 | 2017 |
| Multi-parameter Arnoldi-Tikhonov methods S Gazzola, P Novati Electronic Transactions on Numerical Analysis 40, 452-475, 2013 | 34 | 2013 |
| Computational methods for large-scale inverse problems: a survey on hybrid projection methods J Chung, S Gazzola Siam Review 66 (2), 205-284, 2024 | 33 | 2024 |
| Krylov methods for inverse problems: Surveying classical, and introducing new, algorithmic approaches S Gazzola, M Sabaté Landman GAMM‐Mitteilungen 43 (4), e202000017, 2020 | 30 | 2020 |
| Embedded techniques for choosing the parameter in Tikhonov regularization S Gazzola, P Novati, MR Russo Numerical Linear Algebra with Applications 21 (6), 796-812, 2014 | 30 | 2014 |
| Flexible GMRES for total variation regularization S Gazzola, M Sabaté Landman BIT Numerical Mathematics 59 (3), 721-746, 2019 | 22 | 2019 |
| On the Lanczos and Golub–Kahan reduction methods applied to discrete ill‐posed problems S Gazzola, E Onunwor, L Reichel, G Rodriguez Numerical Linear Algebra with Applications 23 (1), 187-204, 2016 | 21 | 2016 |
| Arnoldi decomposition, GMRES, and preconditioning for linear discrete ill-posed problems S Gazzola, S Noschese, P Novati, L Reichel Applied Numerical Mathematics 142, 102-121, 2019 | 19 | 2019 |
| Inheritance of the discrete Picard condition in Krylov subspace methods S Gazzola, P Novati BIT Numerical Mathematics 56 (3), 893-918, 2016 | 19 | 2016 |
| Iteratively reweighted FGMRES and FLSQR for sparse reconstruction S Gazzola, JG Nagy, MS Landman SIAM Journal on Scientific Computing 43 (5), S47-S69, 2021 | 18 | 2021 |
| A new framework for multi-parameter regularization S Gazzola, L Reichel BIT Numerical Mathematics 56 (3), 919-949, 2016 | 18 | 2016 |
| On the block Lanczos and block Golub–Kahan reduction methods applied to discrete ill‐posed problems A Alqahtani, S Gazzola, L Reichel, G Rodriguez Numerical Linear Algebra with Applications 28 (5), e2376, 2021 | 16 | 2021 |
| An inner–outer iterative method for edge preservation in image restoration and reconstruction S Gazzola, ME Kilmer, JG Nagy, O Semerci, EL Miller Inverse Problems 36 (12), 124004, 2020 | 13 | 2020 |
| Efficient learning methods for large-scale optimal inversion design J Chung, M Chung, S Gazzola, M Pasha arXiv preprint arXiv:2110.02720, 2021 | 11 | 2021 |
| Regularization techniques based on Krylov methods for ill-posed linear systems S Gazzola Ph. D. thesis, Dept. of Mathematics, University of Padua, Italy, 2014 | 7 | 2014 |
James NagyProfessor of Mathematics and Computer Science, Emory University在 emory.edu 的电子邮件经过验证
