3 papers
cs.LG2026
Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves
Alessio Borgi, Fabrizio Silvestri, Pietro Liò
Sheaf Neural Networks equip graph structures with a cellular sheaf: a geometric structure which assigns local vector spaces (stalks) and a linear learnable restriction/transport ma…
cs.LG2025
Symmetry and Generalisation in Neural Approximations of Renormalisation Transformations
Cassidy Ashworth, Pietro Liò, Francesco Caso
Deep learning models have proven enormously successful at using multiple layers of representation to learn relevant features of structured data. Encoding physical symmetries into t…
cs.LG2025
Renormalized Graph Representations for Node Classification
Francesco Caso, Giovanni Trappolini, Andrea Bacciu +2
Graph neural networks process information on graphs represented at a given resolution scale. We analyze the effect of using different coarse-grained graph resolutions, obtained thr…