F. Besold (Humboldt-Universität zu Berlin)
Tuesday, December 12, 2017 - 15:00
Mohrenstr. 39, 10117 Berlin, Weierstraß-Hörsaal (Raum: 406), 4. Etage
Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
In this talk we introduce persistence diagrams. These can be used as a tool to infer topological information from noisy data. To do that, we review simplicial and singular homology. Persistence diagrams have originally be defined for functions on topological spaces, but can be more generally defined using persistence modules. Stability results ensuring that close data sets have close persistence diagrams show that persistence diagrams are well-suited to deal with real-life data. Applications include data smoothing or recovering topological features of manifolds from a sampled point cloud.
submitted by chschnei (christine.schneider@wias-berlin.de, 030 20372574)