32 citations · 69 across the 25 of their papers we have counts for
4 papers · 1 filter
A Sheaf Theoretical Approach to Uncertainty Quantification of Heterogeneous Geolocation Information
Cliff Joslyn, Lauren Charles, Chris DePerno +7
Integration of heterogeneous sensors is a challenging problem across a range of applications. Prominent among these are multi-target tracking, where one must combine observations f…
Relative Hausdorff Distance for Network Analysis
Sinan G. Aksoy, Kathleen E. Nowak, Emilie Purvine +1
Similarity measures are used extensively in machine learning and data science algorithms. The newly proposed graph Relative Hausdorff (RH) distance is a lightweight yet nuanced sim…
Hypernetwork Science via High-Order Hypergraph Walks
Sinan G. Aksoy, Cliff Joslyn, Carlos Ortiz Marrero +2
We propose high-order hypergraph walks as a framework to generalize graph-based network science techniques to hypergraphs. Edge incidence in hypergraphs is quantitative, yielding h…
Local Versus Global Distances for Zigzag Persistence Modules
Ellen Gasparovic, Maria Gommel, Emilie Purvine +4
This short note establishes explicit and broadly applicable relationships between persistence-based distances computed locally and globally. In particular, we show that the bottlen…