7 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…
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-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…