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ORCIDFederico Benvenuto
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2020 – today
- 2024
[j7]Silvia Berra, Alessandro La Torraca, Federico Benvenuto, Sara Sommariva
:
Combined Newton-Gradient Method for Constrained Root-Finding in Chemical Reaction Networks. J. Optim. Theory Appl. 200(1): 404-427 (2024)- [j6]Sabrina Guastavino, Michele Piana, Federico Benvenuto:
Bad and Good Errors: Value-Weighted Skill Scores in Deep Ensemble Learning. IEEE Trans. Neural Networks Learn. Syst. 35(2): 1993-2002 (2024) - [i18]Michele Piana, Federico Benvenuto, Anna Maria Massone, Cristina Campi, Sabrina Guastavino, Francesco Marchetti, Paolo Massa, Emma Perracchione, Anna Volpara:
AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data. CoRR abs/2401.01104 (2024) - 2023
- [i17]Sabrina Guastavino, Valentina Candiani, Alessandro Bemporad, Francesco Marchetti, Federico Benvenuto, Anna Maria Massone, Roberto Susino, Daniele Telloni, Silvano Fineschi, Michele Piana:
Physics-driven machine learning for the prediction of coronal mass ejections' travel times. CoRR abs/2305.10057 (2023) - [i16]Francesco Marchetti, Sabrina Guastavino, Cristina Campi, Federico Benvenuto, Michele Piana:
A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics. CoRR abs/2305.13472 (2023) - [i15]Chiara Razzetta, Valentina Candiani, Marco Crocco, Federico Benvenuto:
A hybrid time-frequency parametric modelling of medical ultrasound signal transmission. CoRR abs/2305.18173 (2023) - 2022
- [i14]Anna Volpara, Paolo Massa, Emma Perracchione, Andrea Francesco Battaglia, Sara Garbarino, Federico Benvenuto, Anna Maria Massone, Sam Krucker, Michele Piana:
Forward-fitting STIX visibilities. CoRR abs/2204.14148 (2022) - [i13]Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto, Cristina Campi, Michele Piana:
Operational solar flare forecasting via video-based deep learning. CoRR abs/2209.05128 (2022) - [i12]Chiara Razzetta, Marco Crocco, Federico Benvenuto:
Narrowband Transmit Beam Pattern in medical ultrasound: a stochastic approach to delays optimization. CoRR abs/2209.05758 (2022) - [i11]Silvia Berra, Alessandro La Torraca, Federico Benvenuto, Sara Sommariva:
A fast and convergent combined Newton and gradient descent method for computing steady states of chemical reaction networks. CoRR abs/2212.14252 (2022) - 2021
- [i10]Sabrina Guastavino, Michele Piana, Federico Benvenuto:
Bad and good errors: value-weighted skill scores in deep ensemble learning. CoRR abs/2103.02881 (2021) - [i9]Paolo Massa, Emma Perracchione, Sara Garbarino, Andrea F. Battaglia, Federico Benvenuto, Michele Piana, Gordon Hurford, Sam Krucker:
Imaging from STIX visibility amplitudes. CoRR abs/2108.04901 (2021) - [i8]Sabrina Guastavino, Michele Piana, Marco Tizzi, Federico Cassola, Antonio Iengo, Davide Sacchetti, Enrico Solazzo, Federico Benvenuto:
Prediction of severe thunderstorm events with ensemble deep learning and radar data. CoRR abs/2109.09791 (2021) - [i7]Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto, Cristina Campi, Michele Piana:
Implementation paradigm for supervised flare forecasting studies: a deep learning application with video data. CoRR abs/2110.12554 (2021) - [i6]Paolo Massa, Sara Garbarino, Federico Benvenuto:
Regularization from examples via neural networks for parametric inverse problems: topology matters. CoRR abs/2112.11331 (2021) - 2020
- [j5]Sabrina Guastavino, Federico Benvenuto:
Convergence Rates of Spectral Regularization Methods: A Comparison between Ill-Posed Inverse Problems and Statistical Kernel Learning. SIAM J. Numer. Anal. 58(6): 3504-3529 (2020) - [i5]Federico Benvenuto, Cristina Campi, Anna Maria Massone, Michele Piana:
Machine learning as a flaring storm warning machine: Was a warning machine for the September 2017 solar flaring storm possible? CoRR abs/2007.02425 (2020) - [i4]Paolo Massa, Federico Benvenuto:
Predictive risk estimation for the Expectation Maximization algorithm with Poisson data. CoRR abs/2011.05965 (2020)
2010 – 2019
- 2019
- [j4]Federico Benvenuto, Cristina Campi:
A discrepancy principle for the Landweber iteration based on risk minimization. Appl. Math. Lett. 96: 1-6 (2019) - [j3]Sabrina Guastavino, Federico Benvenuto:
A consistent and numerically efficient variable selection method for sparse Poisson regression with applications to learning and signal recovery. Stat. Comput. 29(3): 501-516 (2019) - [i3]Sabrina Guastavino, Michele Piana, Anna Maria Massone, Richard A. Schwartz, Federico Benvenuto:
Desaturating EUV observations of solar flaring storms. CoRR abs/1904.04211 (2019) - [i2]Federico Benvenuto, Bangti Jin:
A Parameter Choice Rule for Tikhonov Regularization Based on Predictive Risk. CoRR abs/1912.13004 (2019) - 2018
- [c2]Michele Piana, Federico Benvenuto, Anna Maria Massone, Cristina Campi:
FLARECAST: An I4.0 Technology for Space Weather Using Satellite Data. RTSI 2018: 1-4 - 2017
- [j2]Federico Benvenuto:
A Study on Regularization for Discrete Inverse Problems with Model-Dependent Noise. SIAM J. Numer. Anal. 55(5): 2187-2203 (2017) - [i1]Federico Benvenuto, Michele Piana, Cristina Campi, Anna Maria Massone:
A hybrid supervised/unsupervised machine learning approach to solar flare prediction. CoRR abs/1706.07103 (2017) - 2016
- [j1]Federico Benvenuto, Houssem Haddar, Blandine Lantz:
A Robust Inversion Method According to a New Notion of Regularization for Poisson Data with an Application to Nanoparticle Volume Determination. SIAM J. Appl. Math. 76(1): 276-292 (2016)
2000 – 2009
- 2009
- [c1]Silvia Bonettini, Federico Benvenuto, Riccardo Zanella, Luca Zanni, Mario Bertero:
Gradient projection approaches for optimization problems in image deblurring and denoising. EUSIPCO 2009: 1384-1388
Coauthor Index
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