11 citations · 17 across the 7 of their papers we have counts for
11 papers
Persistence-based operators in machine learning
Mattia G. Bergomi, Massimo Ferri, Alessandro Mella +1
Artificial neural networks can learn complex, salient data features to achieve a given task. On the opposite end of the spectrum, mathematically grounded methods such as topologica…
Generalized Permutants and Graph GENEOs
Faraz Ahmad, Massimo Ferri, Patrizio Frosini
In this paper we establish a bridge between Topological Data Analysis and Geometric Deep Learning, adapting the topological theory of group equivariant non-expansive operators (GEN…
Steady and ranging sets in graph persistence
Mattia G. Bergomi, Massimo Ferri, Antonella Tavaglione
Topological data analysis can provide insight on the structure of weighted graphs and digraphs. However, some properties underlying a given (di)graph are hardly mappable to simplic…
Beyond topological persistence: Starting from networks
Mattia G. Bergomi, Massimo Ferri, Pietro Vertechi +1
Persistent homology enables fast and computable comparison of topological objects. However, it is naturally limited to the analysis of topological spaces. We extend the theory of p…
Symmetric functions for fast image retrieval with persistent homology
Alessia Angeli, Massimo Ferri, Ivan Tomba
Persistence diagrams, combining geometry and topology for an effective shape description used in pattern recognition, have already proven to be an effective tool for shape represen…
Topological Graph Persistence
Mattia G. Bergomi, Massimo Ferri, Lorenzo Zuffi
Graphs are a basic tool for the representation of modern data. The richness of the topological information contained in a graph goes far beyond its mere interpretation as a one-dim…