A singular Riemannian geometry approach to Deep Neural Networks I. Theoretical foundations. - Alessandro Benfenati; Alessio Marta (Neural Networks, 2023)

A singular Riemannian geometry approach to deep neural networks II. Reconstruction of 1-D equivalence classes. - Alessandro Benfenati; Alessio Marta (Neural Networks, 2023)

A singular Riemannian Geometry Approach to Deep Neural Networks III. Piecewise Differentiable Layers and Random Walks on n-dimensional Classes. - Alessandro Benfenati; Alessio Marta (CoRR, 2024)

Unveiling Transformer Perception by Exploring Input Manifolds. - Alessandro Benfenati; Alfio Ferrara; Alessio Marta; Davide Riva; Elisabetta Rocchetti (CoRR, 2024)

Estimating Dataset Dimension via Singular Metrics under the Manifold Hypothesis: Application to Inverse Problems. - Paola Causin; Alessio Marta (CoRR, 2025)