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Found 6 papers, 4 papers with code
Euler Characteristic Curves and Profiles: a stable shape invariant for big data problems
While being a weaker invariant in one dimension, we show that Euler Characteristic based approaches do not possess some handicaps of persistent homology; we show efficient algorithms to compute them in a distributed way, their generalization to multifiltrations and practical applicability for big data problems.
Mapper-type algorithms for complex data and relations
Mapper and Ball Mapper are Topological Data Analysis tools used for exploring high dimensional point clouds and visualizing scalar-valued functions on those point clouds.
Hotspot identification for Mapper graphs
Mapper algorithm can be used to build graph-based representations of high-dimensional data capturing structurally interesting features such as loops, flares or clusters.
Ball mapper: a shape summary for topological data analysis
Topological data analysis provides a collection of tools to encapsulate and summarize the shape of data.
Algebraic Topology
Persistence Bag-of-Words for Topological Data Analysis
Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs).
Topology preserving thinning for cell complexes
This paper introduces a novel topology preserving thinning algorithm which removes \textit{simple cells}---a generalization of simple points---of a given cell complex.
