no code implementations • 11 Mar 2024 • Eva Fluck, Sandra Kiefer, Christoph Standke
In recent years, they have also been discovered as a link between structural graph theory and data science: when interpreting similarity in data sets as connectivity between points, finding clusters in the data essentially amounts to finding tangles in the underlying graphs.
1 code implementation • 25 Mar 2022 • Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh
While (message-passing) graph neural networks have clear limitations in approximating permutation-equivariant functions over graphs or general relational data, more expressive, higher-order graph neural networks do not scale to large graphs.
