| Krylov methods for inverse problems: Surveying classical, and introducing new, algorithmic approaches S Gazzola, M Sabaté Landman GAMM‐Mitteilungen 43 (4), e202000017, 2020 | 34 | 2020 |
| Flexible GMRES for total variation regularization S Gazzola, M Sabaté Landman BIT Numerical Mathematics 59, 721-746, 2019 | 23 | 2019 |
| Iteratively reweighted FGMRES and FLSQR for sparse reconstruction S Gazzola, JG Nagy, MS Landman SIAM Journal on Scientific Computing 43 (5), S47-S69, 2021 | 20 | 2021 |
| On Krylov methods for large-scale CBCT reconstruction MS Landman, A Biguri, S Hatamikia, R Boardman, J Aston, CB Schönlieb Physics in Medicine & Biology 68 (15), 155008, 2023 | 6 | 2023 |
| Regularization by inexact Krylov methods with applications to blind deblurring S Gazzola, MS Landman SIAM Journal on Matrix Analysis and Applications 42 (4), 1528-1552, 2021 | 5 | 2021 |
| A study of why we need to reassess full reference image quality assessment with medical images A Breger, A Biguri, MS Landman, I Selby, N Amberg, E Brunner, J Gröhl, ... arXiv preprint arXiv:2405.19097, 2024 | 3 | 2024 |
| Optimal Sparse Energy Sampling for X-ray Spectro-Microscopy: Reducing the X-ray Dose and Experiment Time Using Model Order Reduction PD Quinn, M Sabaté Landman, T Davis, M Freitag, S Gazzola, S Dolgov Chemical & Biomedical Imaging 2 (4), 283-292, 2024 | 3 | 2024 |
| Latent-space disentanglement with untrained generator networks for the isolation of different motion types in video data A Abdullah, M Holler, K Kunisch, MS Landman International Conference on Scale Space and Variational Methods in Computer …, 2023 | 2 | 2023 |
| H-CMRH: a novel inner product free hybrid Krylov method for large-scale inverse problems AN Brown, MS Landman, JG Nagy arXiv preprint arXiv:2401.06918, 2024 | 1 | 2024 |
| Autonomous Exploration and Identification of High Performing Adsorbents using Active Learning G Donval, C Hand, J Hook, E Dupont, MS Landman, M Freitag, M Lennox, ... | 1 | 2021 |
| H-CMRH: An Inner Product Free Hybrid Krylov Method for Large-Scale Inverse Problems AN Brown, M Sabaté Landman, JG Nagy SIAM Journal on Matrix Analysis and Applications 46 (1), 232-255, 2025 | | 2025 |
| TIGRE v3: Efficient and easy to use iterative computed tomographic reconstruction toolbox for real datasets A Biguri, T Sadakane, R Lindroos, Y Liu, MS Landman, Y Du, M Lohvithee, ... arXiv preprint arXiv:2412.10129, 2024 | | 2024 |
| A joint reconstruction and model selection approach for large-scale linear inverse modeling (msHyBR v2) M Sabaté Landman, J Chung, J Jiang, SM Miller, AK Saibaba Geoscientific Model Development 17 (23), 8853-8872, 2024 | | 2024 |
| Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation J Chung, SM Miller, MS Landman, AK Saibaba arXiv preprint arXiv:2412.02773, 2024 | | 2024 |
| Flexible Krylov methods for group sparsity regularization J Chung, MS Landman Physica Scripta 99 (12), 125006, 2024 | | 2024 |
| Inner Product Free Krylov Methods for Large-Scale Inverse Problems AN Brown, J Chung, JG Nagy, MS Landman arXiv preprint arXiv:2409.05239, 2024 | | 2024 |
| A Joint Reconstruction and Model Selection Approach for Large Scale Inverse Modeling M Sabaté Landman, J Chung, J Jiang, S Miller, A Saibaba Geoscientific Model Development Discussions 2024, 1-29, 2024 | | 2024 |
| Augmented flexible Krylov subspace methods with applications to Bayesian inverse problems MS Landman, J Jiang, J Zhang, W Ren Linear Algebra and its Applications, 2024 | | 2024 |
| Augmented Flexible Krylov Subspace methods with applications to Bayesian inverse problems M Sabate Landman, J Jiang, J Zhang, W Ren arXiv e-prints, arXiv: 2310.05285, 2023 | | 2023 |
| Nonlinear motion separation via untrained generator networks with disentangled latent space variables and applications to cardiac MRI. M Holler, K Kunisch, MS Landman arXiv preprint arXiv:2205.10367, 2022 | | 2022 |