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
48 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
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
24 2019 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
23 2020 Residual whiteness principle for parameter-free image restoration A Lanza, M Pragliola, F Sgallari
Electronic Transactions on Numerical Analysis 53, 329-351, 2020
18 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 Space-variant generalised Gaussian regularisation for image restoration A Lanza, S Morigi, M Pragliola, F Sgallari
Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018
12 2018 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
10 2023 Overcomplete representation in a hierarchical Bayesian framework M Pragliola, D Calvetti, E Somersalo
arXiv preprint arXiv:2006.13524, 2020
10 2020 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
7 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 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
5 2023 Residual Whiteness Principle for Automatic Parameter Selection in M Pragliola, L Calatroni, A Lanza, F Sgallari
International Conference on Scale Space and Variational Methods in Computer …, 2021
5 2021 Towards 3D-printed steel grid-shells: the main idea and first studies V Laghi, M Palermo, M Pragliola, VA Girelli, G Van Der Velden, ...
Proceedings of IASS Annual Symposia 2018 (9), 1-8, 2018
5 2018 A comparison of parameter choice rules for A Buccini, M Pragliola, L Reichel, F Sgallari
ANNALI DELL'UNIVERSITA'DI FERRARA 68 (2), 441-463, 2022
4 2022 Automatic fidelity and regularization terms selection in variational image restoration A Lanza, M Pragliola, F Sgallari
BIT Numerical Mathematics 62 (3), 931-964, 2022
4 2022 Computational issues in linear multistep method particle filtering D Calvetti, S Cuomo, M Pragliola, E Somersalo, G Toraldo
AIP Conference Proceedings 1776 (1), 2016
4 2016 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
3 2023 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
3 2023 