1 citations · 1 across the 4 of their papers we have counts for
4 papers
Internal Evaluation of Density-Based Clusterings with Noise
Anna Beer, Lena Krieger, Pascal Weber +3
Being able to evaluate the quality of a clustering result even in the absence of ground truth cluster labels is fundamental for research in data mining. However, most cluster valid…
Ultrametric Cluster Hierarchies: I Want 'em All!
Andrew Draganov, Pascal Weber, Rasmus Skibdahl Melanchton Jørgensen +3
Hierarchical clustering is a powerful tool for exploratory data analysis, organizing data into a tree of clusterings from which a partition can be chosen. This paper generalizes th…
SHADE: Deep Density-based Clustering
Anna Beer, Pascal Weber, Lukas Miklautz +4
Detecting arbitrarily shaped clusters in high-dimensional noisy data is challenging for current clustering methods. We introduce SHADE (Structure-preserving High-dimensional Analys…
Temporal Subspace Clustering for Molecular Dynamics Data
Anna Beer, Martin Heinrigs, Claudia Plant +1
We introduce MOSCITO (MOlecular Dynamics Subspace Clustering with Temporal Observance), a subspace clustering for molecular dynamics data. MOSCITO groups those timesteps of a molec…