2 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2022★ 2 cited
A geometric framework for outlier detection in high-dimensional data
Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
Outlier or anomaly detection is an important task in data analysis. We discuss the problem from a geometrical perspective and provide a framework that exploits the metric structure…
cs.LG2022★ 1 cited
Enhancing cluster analysis via topological manifold learning
Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl +1
We discuss topological aspects of cluster analysis and show that inferring the topological structure of a dataset before clustering it can considerably enhance cluster detection: t…