Hourglass Persistence interleaves sequences of graph inclusions and contractions to produce more expressive topological features than standard persistent homology for learning on graphs and higher-order complexes.
If there is still a non-zero vectorwinH k(X0), we pickwand repeat the process (if the linear map sendswoutside
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Contraction and Hourglass Persistence for Learning on Graphs, Simplices, and Cells
Hourglass Persistence interleaves sequences of graph inclusions and contractions to produce more expressive topological features than standard persistent homology for learning on graphs and higher-order complexes.