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
244 2019 On Krylov projection methods and Tikhonov regularization S Gazzola, P Novati, MR Russo
Electron. Trans. Numer. Anal 44 (1), 83-123, 2015
127 2015 Generalized Arnoldi--Tikhonov Method for Sparse Reconstruction S Gazzola, JG Nagy
SIAM Journal on Scientific Computing 36 (2), B225-B247, 2014
81 2014 Flexible Krylov Methods for J Chung, S Gazzola
SIAM Journal on Scientific Computing 41 (5), S149-S171, 2019
48 2019 Computational methods for large-scale inverse problems: a survey on hybrid projection methods J Chung, S Gazzola
Siam Review 66 (2), 205-284, 2024
47 2024 Automatic parameter setting for Arnoldi–Tikhonov methods S Gazzola, P Novati
Journal of Computational and Applied Mathematics 256, 180-195, 2014
46 2014 Fast nonnegative least squares through flexible Krylov subspaces S Gazzola, Y Wiaux
SIAM Journal on Scientific Computing 39 (2), A655-A679, 2017
41 2017 Krylov methods for inverse problems: Surveying classical, and introducing new, algorithmic approaches S Gazzola, M Sabaté Landman
GAMM‐Mitteilungen 43 (4), e202000017, 2020
35 2020 Multi-parameter Arnoldi-Tikhonov methods S Gazzola, P Novati
Electronic Transactions on Numerical Analysis 40, 452-475, 2013
34 2013 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
24 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
22 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
21 2021 Inheritance of the discrete Picard condition in Krylov subspace methods S Gazzola, P Novati
BIT Numerical Mathematics 56 (3), 893-918, 2016
20 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 A new framework for multi-parameter regularization S Gazzola, L Reichel
BIT Numerical Mathematics 56 (3), 919-949, 2016
19 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
16 2020 A computational framework for edge-preserving regularization in dynamic inverse problems M Pasha, AK Saibaba, S Gazzola, MI Español, E de Sturler
Electronic Transactions on Numerical Analysis 58, 486-516, 2023
12 2023 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 
James NagyProfessor of Mathematics and Computer Science, Emory UniversityEmail verificata su emory.edu
