2024
Graphcode: Learning from multiparameter persistent homology using graph neural networks
NeurIPS 2024poster
We introduce graphcodes, a novel multi-scale summary of the topological properties of a dataset that is based on the well-established theory of persistent homology. Graphcodes handle datasets that are filtered along two real-valued scale parameters. Such multi-parameter topological summaries are usu…