14 citations · 25 across the 4 of their papers we have counts for
5 papers
Generating Graphs via Spectral Diffusion
Giorgia Minello, Alessandro Bicciato, Luca Rossi +2
In this paper, we present GGSD, a novel graph generative model based on 1) the spectral decomposition of the graph Laplacian matrix and 2) a diffusion process. Specifically, we pro…
GNN-LoFI: a Novel Graph Neural Network through Localized Feature-based Histogram Intersection
Alessandro Bicciato, Luca Cosmo, Giorgia Minello +2
Graph neural networks are increasingly becoming the framework of choice for graph-based machine learning. In this paper, we propose a new graph neural network architecture that sub…
LDA2Net: Digging under the surface of COVID-19 topics in scientific literature
Giorgia Minello, Carlo R. M. A. Santagiustina, Massimo Warglien
During the COVID-19 pandemic, the scientific literature related to SARS-COV-2 has been growing dramatically, both in terms of the number of publications and of its impact on people…
Graph Kernel Neural Networks
Luca Cosmo, Giorgia Minello, Alessandro Bicciato +4
The convolution operator at the core of many modern neural architectures can effectively be seen as performing a dot product between an input matrix and a filter. While this is rea…
On the Von Neumann Entropy of Graphs
Giorgia Minello, Luca Rossi, Andrea Torsello
The von Neumann entropy of a graph is a spectral complexity measure that has recently found applications in complex networks analysis and pattern recognition. Two variants of the v…