177 citations · 661 across the 41 of their papers we have counts for
42 papers
Weak convergence rates for spectral regularization via sampling inequalities
Sabrina Guastavino, Gabriele Santin, Francesco Marchetti +1
Convergence rates in spectral regularization methods quantify the approximation error in inverse problems as a function of the noise level or the number of sampling points. Classic…
PRESOL: a web-based computational setting for feature-based flare forecasting
Chiara Curletto, Paolo Massa, Valeria Tagliafico +4
Solar flares are the most explosive phenomena in the solar system and the main trigger of the events' chain that starts from Coronal Mass Ejections and leads to geomagnetic storms…
AI-based modular warning machine for risk identification in proximity healthcare
Chiara Razzetta, Shahryar Noei, Federico Barbarossa +17
"DHEAL-COM - Digital Health Solutions in Community Medicine" is a research and technology project funded by the Italian Department of Health for the development of digital solution…
Convergence rates for Tikhonov regularization on compact sets: application to neural networks
Barbara Palumbo, Paolo Massa, Federico Benvenuto
In this work, we consider ill-posed inverse problems in which the forward operator is continuous and weakly closed, and the sought solution belongs to a weakly closed constraint se…
Solving Implicit Inverse Problems with Homotopy-Based Regularization Path
Davide Parodi, Federico Benvenuto, Sara Garbarino +1
Implicit inverse problems, in which noisy observations of a physical quantity are used to infer a nonlinear functional applied to an associated function, are inherently ill posed a…
Physics-informed features in supervised machine learning
Margherita Lampani, Sabrina Guastavino, Michele Piana +1
Supervised machine learning involves approximating an unknown functional relationship from a limited dataset of features and corresponding labels. The classical approach to feature…
When algebra twinks system biology: a conjecture on the structure of Gröbner bases in complex chemical reaction networks
Paola Ferrari, Sara Sommariva, Michele Piana +2
We address the challenge of identifying all real positive steady states in chemical reaction networks (CRNs) governed by mass-action kinetics. Traditional numerical methods often r…
AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data
Michele Piana, Federico Benvenuto, Anna Maria Massone +6
AI-FLARES (Artificial Intelligence for the Analysis of Solar Flares Data) is a research project funded by the Agenzia Spaziale Italiana and by the Istituto Nazionale di Astrofisica…
CAESAR: Space Weather archive prototype for ASPIS
Marco Molinaro, Valerio Formato, Carmelo Magnafico +18
The project CAESAR (Comprehensive spAce wEather Studies for the ASPIS prototype Realization) is aimed to tackle all the relevant aspects of Space Weather (SWE) and realize the prot…
A hybrid time-frequency parametric modelling of medical ultrasound signal transmission
Chiara Razzetta, Valentina Candiani, Marco Crocco +1
Medical ultrasound imaging is the most widespread real-time non-invasive imaging system and its formulation comprises signal transmission, signal reception, and image formation. Ul…
A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics
Francesco Marchetti, Sabrina Guastavino, Cristina Campi +2
In many contexts, customized and weighted classification scores are designed in order to evaluate the goodness of the predictions carried out by neural networks. However, there exi…
Physics-driven machine learning for the prediction of coronal mass ejections' travel times
Sabrina Guastavino, Valentina Candiani, Alessandro Bemporad +7
Coronal Mass Ejections (CMEs) correspond to dramatic expulsions of plasma and magnetic field from the solar corona into the heliosphere. CMEs are scientifically relevant because th…
STIX imaging I -- Concept
Paolo Massa, Gordon. J. Hurford, Anna Volpara +17
Aims. To provide a schematic mathematical description of the imaging concept of the Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter. The derived model is th…
A fast and convergent combined Newton and gradient descent method for computing steady states of chemical reaction networks
Silvia Berra, Alessandro La Torraca, Federico Benvenuto +1
In this work we present a fast, globally convergent, iterative algorithm for computing the asymptotically stable states of nonlinear large--scale systems of quadratic autonomous Or…
Operational solar flare forecasting via video-based deep learning
Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto +2
Operational flare forecasting aims at providing predictions that can be used to make decisions, typically at a daily scale, about the space weather impacts of flare occurrence. Thi…
A stochastic approach to delays optimization for narrowband transmit beam pattern in medical ultrasound
Chiara Razzetta, Valentina Candiani, Marco Crocco +1
Ultrasound imaging is extensively employed in clinical settings due to its non-ionizing nature and real-time capabilities. The beamformer represents a crucial component of an ultra…
Forward-fitting STIX visibilities
Anna Volpara, Paolo Massa, Emma Perracchione +6
Aima. To determine to what extent the problem of forward fitting visibilities measured by the Spectrometer/Telescope Imaging X-rays (STIX) on-board Solar Orbiter is more challengin…
First hard X-ray imaging results by Solar Orbiter STIX
Paolo Massa, Andrea F. Battaglia, Anna Volpara +15
Context. The Spectrometer/Telescope for Imaging X-rays (STIX) is one of 6 remote sensing instruments on-board Solar Orbiter. It provides hard X-ray imaging spectroscopy of solar fl…
Regularization from examples via neural networks for parametric inverse problems: topology matters
Paolo Massa, Sara Garbarino, Federico Benvenuto
In this work we deal with parametric inverse problems, which consist in recovering a finite number of parameters describing the structure of an unknown object, from indirect measur…
Implementation paradigm for supervised flare forecasting studies: a deep learning application with video data
Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto +2
Solar flare forecasting can be realized by means of the analysis of magnetic data through artificial intelligence techniques. The aim is to predict whether a magnetic active region…
Prediction of severe thunderstorm events with ensemble deep learning and radar data
Sabrina Guastavino, Michele Piana, Marco Tizzi +5
The problem of nowcasting extreme weather events can be addressed by applying either numerical methods for the solution of dynamic model equations or data-driven artificial intelli…
Imaging from STIX visibility amplitudes
Paolo Massa, Emma Perracchione, Sara Garbarino +5
Aims: To provide the first demonstration of STIX Fourier-transform X-ray imaging using semi-calibrated (amplitude-only) visibility data acquired during the Solar Orbiter's cruise p…
STIX X-ray microflare observations during the Solar Orbiter commissioning phase
Andrea Francesco Battaglia, Jonas Saqri, Paolo Massa +34
The Spectrometer/Telescope for Imaging X-rays (STIX) is the HXR instrument onboard Solar Orbiter designed to observe solar flares over a broad range of flare sizes, between 4-150 k…
The Flare Likelihood and Region Eruption Forecasting (FLARECAST) Project: Flare forecasting in the big data & machine learning era
M. K. Georgoulis, D. S. Bloomfield, M. Piana +25
The EU funded the FLARECAST project, that ran from Jan 2015 until Feb 2018. FLARECAST had a R2O focus, and introduced several innovations into the discipline of solar flare forecas…