3 papers
stat.ML2026
TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
Matteo Biagetti, Mathieu Carrière, Francesco Conti +3
Persistence diagrams provide stable, interpretable summaries of geometric and topological structure and are useful for simulation-based inference when low-order statistics miss key…
math.RT2026
An Algebraic Representation Theorem for Linear GENEOs in Geometric Machine Learning
Francesco Conti, Patrizio Frosini, Nicola Quercioli
Geometric and Topological Deep Learning are rapidly growing research areas that enhance machine learning through the use of geometric and topological structures. Within this framew…
cs.LG2025
Reconstruction of SINR Maps from Sparse Measurements using Group Equivariant Non-Expansive Operators
Lorenzo Mario Amorosa, Francesco Conti, Nicola Quercioli +4
As sixth generation (6G) wireless networks evolve, accurate signal-to-interference-noise ratio (SINR) maps are becoming increasingly critical for effective resource management and…