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ORCIDMonica Pragliola
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2020 – today
- 2024
[j8]Davide Elia De Falco, Francesco Calabrò
, Monica Pragliola:
Insights on the different convergences in Extreme Learning Machine. Neurocomputing 599: 128061 (2024)- [c3]Carlo Santambrogio, Monica Pragliola, Alessandro Lanza, Marco Donatelli, Luca Calatroni:
Whiteness-Based Bilevel Learning of Regularization Parameters in Imaging. EUSIPCO 2024: 1801-1805 - [i14]Carlo Santambrogio, Monica Pragliola, Alessandro Lanza, Marco Donatelli, Luca Calatroni:
Whiteness-based bilevel learning of regularization parameters in imaging. CoRR abs/2403.07026 (2024) - [i13]Daniela Calvetti, Monica Pragliola, Erkki Somersalo:
Sparsity-promoting hierarchical Bayesian model for EIT with a blocky target. CoRR abs/2404.19115 (2024) - [i12]Monica Pragliola, Daniela Calvetti, Erkki Somersalo:
An efficient hierarchical Bayesian method for the Kuopio tomography challenge 2023. CoRR abs/2405.03343 (2024) - 2023
- [j7]Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
ADMM-Based Residual Whiteness Principle for Automatic Parameter Selection in Single Image Super-Resolution Problems. J. Math. Imaging Vis. 65(1): 99-123 (2023) - [j6]Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
On and Beyond Total Variation Regularization in Imaging: The Role of Space Variance. SIAM Rev. 65(3): 601-685 (2023) - [i11]Tatiana A. Bubba, Luca Calatroni, Ambra Catozzi, Serena Crisci, Thomas Pock, Monica Pragliola, Siiri Rautio, Danilo Riccio, Andrea Sebastiani:
Bilevel learning of regularization models and their discretization for image deblurring and super-resolution. CoRR abs/2302.10056 (2023) - 2022
- [j5]Francesca Bevilacqua, Alessandro Lanza, Monica Pragliola, Fiorella Sgallari:
Nearly Exact Discrepancy Principle for Low-Count Poisson Image Restoration. J. Imaging 8(1): 1 (2022) - [i10]Daniela di Serafino, Monica Pragliola:
Automatic parameter selection for the TGV regularizer in image restoration under Poisson noise. CoRR abs/2205.13439 (2022) - [i9]Francesca Bevilacqua, Alessandro Lanza, Monica Pragliola, Fiorella Sgallari:
Whiteness-based parameter selection for Poisson data in variational image processing. CoRR abs/2207.10481 (2022) - 2021
- [c2]Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
Residual Whiteness Principle for Automatic Parameter Selection in ℓ 2-ℓ 2 Image Super-Resolution Problems. SSVM 2021: 476-488 - [i8]Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
Residual whiteness principle for automatic parameter selection in 𝓁2-𝓁2 image super-resolution problems. CoRR abs/2104.01001 (2021) - [i7]Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
On and beyond Total Variation regularisation in imaging: the role of space variance. CoRR abs/2104.03650 (2021) - [i6]Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
ADMM-based residual whiteness principle for automatic parameter selection in super-resolution problems. CoRR abs/2108.13091 (2021) - 2020
- [j4]Daniela Calvetti, Monica Pragliola, Erkki Somersalo:
Sparsity Promoting Hybrid Solvers for Hierarchical Bayesian Inverse Problems. SIAM J. Sci. Comput. 42(6): A3761-A3784 (2020) - [i5]Daniela Calvetti, Monica Pragliola, Erkki Somersalo:
Sparsity promoting hybrid solvers for hierarchical Bayesian inverse problems. CoRR abs/2003.06532 (2020) - [i4]Monica Pragliola, Daniela Calvetti, Erkki Somersalo:
Overcomplete representation in a hierarchical Bayesian framework. CoRR abs/2006.13524 (2020)
2010 – 2019
- 2019
- [j3]Alessandro Lanza, Serena Morigi, Monica Pragliola, Fiorella Sgallari:
Space-variant generalised Gaussian regularisation for image restoration. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 7(5-6): 490-503 (2019) - [j2]Luca Calatroni, Alessandro Lanza, Monica Pragliola, Fiorella Sgallari:
A Flexible Space-Variant Anisotropic Regularization for Image Restoration with Automated Parameter Selection. SIAM J. Imaging Sci. 12(2): 1001-1037 (2019) - [i3]Alessandro Lanza, Serena Morigi, Monica Pragliola, Fiorella Sgallari:
Space-variant Generalized Gaussian Regularization for Image Restoration. CoRR abs/1906.10517 (2019) - [i2]Luca Calatroni, Alessandro Lanza, Monica Pragliola, Fiorella Sgallari:
Space-adaptive anisotropic bivariate Laplacian regularization for image restoration. CoRR abs/1908.00801 (2019) - 2017
- [j1]Salvatore Cuomo, Pasquale De Michele, Monica Pragliola:
A computational scheme to predict dynamics in IoT systems by using particle filter. Concurr. Comput. Pract. Exp. 29(11) (2017) - 2016
- [c1]Salvatore Cuomo, Pasquale De Michele, Monica Pragliola, Gerardo Severino:
Mimic Visiting Styles by Using a Statistical Approach in a Cultural Event Case Study. EUSPN/ICTH 2016: 449-454 - [i1]Daniela Calvetti, Salvatore Cuomo, Monica Pragliola, Erkki Somersalo, Gerardo Toraldo:
Computational issues and numerical experiments for Linear Multistep Method Particle Filtering. CoRR abs/1605.05042 (2016)
Coauthor Index
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