| Sparse reconstructions from few noisy data: analysis of hierarchical Bayesian models with generalized gamma hyperpriors D Calvetti, M Pragliola, E Somersalo, A Strang Inverse Problems 36 (2), 025010, 2020 | 61 | 2020 |
| Sparsity promoting hybrid solvers for hierarchical Bayesian inverse problems D Calvetti, M Pragliola, E Somersalo SIAM Journal on Scientific Computing 42 (6), A3761-A3784, 2020 | 34 | 2020 |
| Adaptive parameter selection for weighted-TV image reconstruction problems L Calatroni, A Lanza, M Pragliola, F Sgallari Journal of Physics: Conference Series 1476 (1), 012003, 2020 | 29 | 2020 |
| A flexible space-variant anisotropic regularization for image restoration with automated parameter selection L Calatroni, A Lanza, M Pragliola, F Sgallari SIAM Journal on Imaging Sciences 12 (2), 1001-1037, 2019 | 26 | 2019 |
| On and beyond total variation regularization in imaging: The role of space variance M Pragliola, L Calatroni, A Lanza, F Sgallari SIAM Review 65 (3), 601-685, 2023 | 23 | 2023 |
| Residual whiteness principle for parameter-free image restoration A Lanza, M Pragliola, F Sgallari Electronic Transactions on Numerical Analysis 53, 329-351, 2020 | 23 | 2020 |
| A computational scheme to predict dynamics in IoT systems by using particle filter S Cuomo, P De Michele, M Pragliola Concurrency and Computation: Practice and Experience 29 (11), e4101, 2017 | 16 | 2017 |
| Space-variant TV regularization for image restoration A Lanza, S Morigi, M Pragliola, F Sgallari European Congress on Computational Methods in Applied Sciences and …, 2017 | 14 | 2017 |
| Overcomplete representation in a hierarchical Bayesian framework M Pragliola, D Calvetti, E Somersalo arXiv preprint arXiv:2006.13524, 2020 | 11 | 2020 |
| Space-variant generalised Gaussian regularisation for image restoration A Lanza, S Morigi, M Pragliola, F Sgallari Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2019 | 11 | 2019 |
| Whiteness-based parameter selection for Poisson data in variational image processing F Bevilacqua, A Lanza, M Pragliola, F Sgallari Applied Mathematical Modelling 117, 197-218, 2023 | 9 | 2023 |
| A comparison of parameter choice rules for - minimization A Buccini, M Pragliola, L Reichel, F Sgallari ANNALI DELL'UNIVERSITA'DI FERRARA 68 (2), 441-463, 2022 | 9 | 2022 |
| ADMM-based residual whiteness principle for automatic parameter selection in single image super-resolution problems M Pragliola, L Calatroni, A Lanza, F Sgallari Journal of Mathematical Imaging and Vision 65 (1), 99-123, 2023 | 8 | 2023 |
| Nearly exact discrepancy principle for low-count Poisson image restoration F Bevilacqua, A Lanza, M Pragliola, F Sgallari Journal of Imaging 8 (1), 1, 2021 | 8 | 2021 |
| Mimic visiting styles by using a statistical approach in a cultural event case study S Cuomo, P De Michele, M Pragliola, G Severino Procedia Computer Science 98, 449-454, 2016 | 7 | 2016 |
| Automatic fidelity and regularization terms selection in variational image restoration A Lanza, M Pragliola, F Sgallari BIT Numerical Mathematics 62 (3), 931-964, 2022 | 6 | 2022 |
| Residual Whiteness Principle for Automatic Parameter Selection in - Image Super-Resolution Problems M Pragliola, L Calatroni, A Lanza, F Sgallari International Conference on Scale Space and Variational Methods in Computer …, 2021 | 6 | 2021 |
| Speckle noise removal via learned variational models S Cuomo, M De Rosa, S Izzo, F Piccialli, M Pragliola Applied Numerical Mathematics 200, 162-178, 2024 | 5 | 2024 |
| Masked unbiased principles for parameter selection in variational image restoration under Poisson noise F Bevilacqua, A Lanza, M Pragliola, F Sgallari Inverse Problems 39 (3), 034002, 2023 | 5 | 2023 |
| Automatic parameter selection for the TGV regularizer in image restoration under Poisson noise D di Serafino, M Pragliola arXiv preprint arXiv:2205.13439, 2022 | 5 | 2022 |
