FATBIRD: A Tool for Flight and Trajectories Analyses of Birds. - Daniyal Kazempour; Anna Beer 001; Friederike Herzog; Daniel Kaltenthaler; Johannes-Y. Lohrer; Thomas Seidl 001 (eScience, 2018)

PARADISO: an interactive approach of parameter selection for the mean shift algorithm. - Daniyal Kazempour; Anna Beer 001; Johannes-Y. Lohrer; Daniel Kaltenthaler; Thomas Seidl 001 (SSDBM, 2018)

Chain-detection for DBSCAN. - Janis Held; Anna Beer 001; Thomas Seidl 001 (BTW (Workshops), 2019)

Rock - Let the points roam to their clusters themselves. - Anna Beer 001; Daniyal Kazempour; Thomas Seidl 001 (EDBT, 2019)

Human Learning in Data Science. - Anna Beer 001; Daniyal Kazempour; Marcel Baur; Thomas Seidl 001 (HCI (34), 2019)

Data on RAILs: On Interactive Generation of Artificial Linear Correlated Data. - Daniyal Kazempour; Anna Beer 001; Thomas Seidl 001 (HCI (34), 2019)

A Generator for Subspace Clusters. - Anna Beer 001; Nadine Sarah Schüler; Thomas Seidl 001 (LWDA, 2019)

CODEC - Detecting Linear Correlations in Dense Clusters using coMAD-based PCA. - Maximilian Archimedes Xaver Hünemörder; Anna Beer 001; Daniyal Kazempour; Thomas Seidl 001 (LWDA, 2019)

Clustering Trend Data Time-Series through Segmentation of FFT-decomposed Signal Constituents. - Daniyal Kazempour; Anna Beer 001; Oliver Schrüfer; Thomas Seidl 001 (LWDA, 2019)

MORe++: k-Means Based Outlier Removal on High-Dimensional Data. - Anna Beer 001; Jennifer Lauterbach; Thomas Seidl 001 (SISAP, 2019)

Graph Ordering and Clustering: A Circular Approach. - Anna Beer 001; Thomas Seidl 001 (SSDBM, 2019)

LUCK- Linear Correlation Clustering Using Cluster Algorithms and a kNN based Distance Function. - Anna Beer 001; Daniyal Kazempour; Lisa Stephan; Thomas Seidl 001 (SSDBM, 2019)

Chain-detection Between Clusters. - Janis Held; Anna Beer 001; Thomas Seidl 001 (Datenbank-Spektrum, 2019)

I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering. - Daniyal Kazempour; Anna Beer 001; Peer Kröger; Thomas Seidl 001 (ICDM (Workshops), 2020)

Grace - Limiting the Number of Grid Cells for Clustering High-Dimensional Data. - Anna Beer 001; Daniyal Kazempour; Julian Busch; Alexander Tekles; Thomas Seidl 001 (LWDA, 2020)

Angle-Based Clustering. - Anna Beer 001; Dominik Seeholzer; Nadine Sarah Schüler; Thomas Seidl 001 (SISAP, 2020)

Orderings of Data - More Than a Tripping Hazard: Visionary. - Anna Beer 001; Valentin Hartmann; Thomas Seidl 001 (SSDBM, 2020)

Cluster Flow - an Advanced Concept for Ensemble-Enabling, Interactive Clustering. - Sandra Obermeier; Anna Beer 001; Florian Wahl; Thomas Seidl 001 (BTW, 2021)

Compound Segmentation via Clustering on Mol2Vec-based Embeddings. - Daniyal Kazempour; Anna Beer 001; Melanie Oelker; Peer Kröger; Thomas Seidl 001 (e-Science, 2021)

KISS - A fast kNN-based Importance Score for Subspaces. - Anna Beer 001; Ekaterina Allerborn; Valentin Hartmann; Thomas Seidl 001 (EDBT, 2021)

LUCKe - Connecting Clustering and Correlation Clustering. - Anna Beer 001; Lisa Stephan; Thomas Seidl 001 (ICDM (Workshops), 2021)

AnyCORE - An Anytime Algorithm for Cluster Outlier REmoval. - Andreas Lohrer; Anna Beer 001; Maximilian Archimedes Xaver Hünemörder; Jenny Lauterbach; Thomas Seidl 001; Peer Kröger (LWDA, 2021)

On the edges of clustering: creating synergies with related problems. - Anna Beer 001 (2021)

SCAR - Spectral Clustering Accelerated and Robustified. - Ellen Hohma; Christian M. M. Frey; Anna Beer 001; Thomas Seidl 001 (Proc. VLDB Endow., 2022)

Connecting the Dots - Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering. - Anna Beer 001; Andrew Draganov; Ellen Hohma; Philipp Jahn 001; Christian M. M. Frey; Ira Assent (KDD, 2023)

Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study. - Theresa Ullmann; Anna Beer 001; Maximilian Hünemörder; Thomas Seidl 001; Anne-Laure Boulesteix (Adv. Data Anal. Classif., 2023)

DROPP: Structure-Aware PCA for Ordered Data: A General Method and its Applications in Climate Research and Molecular Dynamics. - Anna Beer 001; Olivér Palotás; Andrea Maldonado 001; Andrew Draganov; Ira Assent (ICDE, 2024)

SHADE: Deep Density-based Clustering. - Anna Beer 001; Pascal Weber 001; Lukas Miklautz; Collin Leiber; Walid Durani; Christian Böhm 001; Claudia Plant (ICDM, 2024)

FALCUN: A Simple and Efficient Deep Active Learning Strategy. - Sandra Gilhuber; Anna Beer 001; Yunpu Ma; Thomas Seidl 001 (ECML/PKDD (3), 2024)

Data with Density-Based Clusters: A Generator for Systematic Evaluation of Clustering Algorithms. - Philipp Jahn 001; Christian M. M. Frey; Anna Beer 001; Collin Leiber; Thomas Seidl 001 (ECML/PKDD (7), 2024)

Temporal Subspace Clustering for Molecular Dynamics Data. - Anna Beer 001; Martin Heinrigs; Claudia Plant; Ira Assent (CoRR, 2024)

FairDen: Fair Density-Based Clustering. - Lena Krieger 001; Anna Beer 001; Pernille Matthews; Anneka Myrup Thiesson; Ira Assent (ICLR, 2025)

I Want 'Em All (At Once) - Ultrametric Cluster Hierarchies. - Andrew Draganov; Pascal Weber 001; Rasmus Skibdahl Melanchton Jørgensen; Anna Beer 001; Claudia Plant; Ira Assent (CoRR, 2025)

DISCO: Internal Evaluation of Density-Based Clustering. - Anna Beer 001; Lena Krieger 001; Pascal Weber 001; Martin Ritzert; Ira Assent; Claudia Plant (CoRR, 2025)