2 papers
cs.LG2026
Breaking Symmetry Bottlenecks in GNN Readouts
Mouad Talhi, Arne Wolf, Anthea Monod
Graph neural networks (GNNs) are widely used for learning on structured data, yet their ability to distinguish non-isomorphic graphs is fundamentally limited. These limitations are…
math.AT2025
Generalized Persistent Laplacians and their Spectral Properties
Arne Wolf, Jiyu Fan, Anthea Monod
Laplacian operators are classical objects that are fundamental in both pure and applied mathematics and are becoming increasingly prominent in modern computational and data science…