11 citations · 19 across the 3 of their papers we have counts for
3 papers
Quantum Distance Approximation for Persistence Diagrams
Bernardo Ameneyro, Rebekah Herrman, George Siopsis +1
Topological Data Analysis methods can be useful for classification and clustering tasks in many different fields as they can provide two dimensional persistence diagrams that summa…
Quantum Persistent Homology for Time Series
Bernardo Ameneyro, George Siopsis, Vasileios Maroulas
Persistent homology, a powerful mathematical tool for data analysis, summarizes the shape of data through tracking topological features across changes in different scales. Classica…
Quantum Persistent Homology
Bernardo Ameneyro, Vasileios Maroulas, George Siopsis
Persistent homology is a powerful mathematical tool that summarizes useful information about the shape of data allowing one to detect persistent topological features while one adju…