5 papers
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…
Koopman Representations of Dynamic Systems with Control
Craig Bakker, Steven Rosenthal, Kathleen E. Nowak
The design and analysis of optimal control policies for dynamical systems can be complicated by nonlinear dependence in the state variables. Koopman operators have been used to sim…
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…
A linear-time algorithm and analysis of graph Relative Hausdorff distance
Sinan G. Aksoy, Kathleen E. Nowak, Stephen J. Young
Graph similarity metrics serve far-ranging purposes across many domains in data science. As graph datasets grow in size, scientists need comparative tools that capture meaningful d…
On the Structure of Isometrically Embeddable Metric Spaces
Kathleen Nowak, Carlos Ortiz Marrero, Stephen J. Young
Since its popularization in the 1970s the Fiedler vector of a graph has become a standard tool for clustering of the vertices of the graph. Recently, Mendel and Noar, Dumitriu and…