Modern data is astonishing in its variety, and is far removed from anything that could be held in spreadsheet or analysed using traditional methods. Through intense research effort, topology has emerged as a source of novel methodology to provide insight into the structure of very complex, high dimensional data. It provided us with tools like persistent homology, which are used to compute numerical topological characteristics of the data. More recently, these methods have been augmented by geometric insights, which are valuable in capturing the structure of and relationships between complex shapes. In this talk, I will provide an overview of new techniques from topology and geometry and illustrate them on particular examples. One set of data was created through the study of CT scans of human lungs, and another addresses the problem of classification of three-dimensional shapes.
Freitag, den 14. Juni 2019 um 09.00 Uhr, in Mathematikon, INF 205, Konferenzraum, 5. Stock Freitag, den 14. Juni 2019 at 09.00, in Mathematikon, INF 205, Konferenzraum, 5. Stock
Der Vortrag folgt der Einladung von The lecture takes place at invitation by Prof. Peter Albers