6 papers
Graph Neural Networks Trained on Null Signal for Angle Reconstruction in X-ray Polarimetry
Vittorio Latorre, Victor Rodriguez-Fernandez, Alessandro Di Marco +3
Scientific real detectors often produce sparse, irregular data defined on non-Euclidean domains, where conventional convolutional neural networks (CNNs) impose geometric biases tha…
Duality for Non Convex Composite Functions via the Fenchel Rockafellar Perturbation Framework
Vittorio Latorre
We examine the duality theory for a class of non-convex functions obtained by composing a convex function with a continuous one. Using Fenchel duality, we derive a dual problem tha…
On Implicit Concave Structures in Half-Quadratic Methods for Signal Reconstruction
Vittorio Latorre
In this work, we introduce a new class of non-convex functions, called implicit concave functions, which are compositions of a concave function with a continuously differentiable m…
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…
Topology Optimization with Bilevel Knapsack: An Efficient 51 Lines MATLAB Code
Vittorio Latorre
This paper presents an efficient 51 lines Matlab code to solve topology optimization problems. By the fact that the presented code is based on an hard 0-1 optimization method that…
Canonical dual solutions to nonconvex radial basis neural network optimization problem
Vittorio Latorre, David Yang Gao
Radial Basis Functions Neural Networks (RBFNNs) are tools widely used in regression problems. One of their principal drawbacks is that the formulation corresponding to the training…