Topological Methods in Data Analysis - Journal Club (Winter 2019/20)
Topological Data Analysis (TDA) is a recent developmentin mathematics that actually offers real world applications. The basic idea is using a homology theory - called persistent homology - to identify structures in data. However, interpreting these structures is by no means an easy task, and depends on the specific details of the underlying system.
In this journal club we will take a detailed look at foundational articles, specific applications and recent developments in the field.
Coordinates
Wednesday 9.15-11.45h
Mathematikon, Seminar Room 9
Schedule
Date | Topic | Article | Speaker |
---|---|---|---|
16.10. | Organizational Meeting | Michael Bleher /
Daniel Spitz | |
23.10. | An Application of the Mapper Algorithm | M. Nicolau, A. J. Levine, and G. Carlsson (2011)
Topology Based Data Analysis Identifies a Subgroup of Breast Cancers with a Unique Mutational Profile and Excellent Survival [1] |
NA |
30.10. | Stability Theorems | D. Cohen-Steiner, H. Edelsbrunner, and J. Harer (2007)
Stability of Persistence Diagrams [2] |
NA |
6.11. | Stability Theorems II | U. Bauer, M. Lesnick. (2016)
Persistence Diagrams as Diagrams: A Categorification of the Stability Theorem https://arxiv.org/abs/1610.10085v2 |
NA |
13.11. | Statistics of Persistence Diagrams | NA | |
20.11. | NA | NA | NA |
27.11. | NA | NA | NA |