Dip-based Deep Embedded Clustering with k-Estimation. - Collin Leiber; Lena G. M. Bauer; Benjamin Schelling; Christian Böhm 001; Claudia Plant (KDD, 2021)

The DipEncoder: Enforcing Multimodality in Autoencoders. - Collin Leiber; Lena G. M. Bauer; Michael Neumayr; Claudia Plant; Christian Böhm 001 (KDD, 2022)

Automatic Parameter Selection for Non-Redundant Clustering. - Collin Leiber; Dominik Mautz; Claudia Plant; Christian Böhm 001 (SDM, 2022)

Application of Deep Clustering Algorithms. - Collin Leiber; Lukas Miklautz; Claudia Plant; Christian Böhm 001 (CIKM, 2023)

Non-Redundant Image Clustering of Early Medieval Glass Beads. - Lukas Miklautz; Andrii Shkabrii; Collin Leiber; Bendeguz Tobias; Benedict Seidl; Elisabeth Weissensteiner; Andreas Rausch 001; Christian Böhm 001; Claudia Plant (DSAA, 2023)

Benchmarking Deep Clustering Algorithms With ClustPy. - Collin Leiber; Lukas Miklautz; Claudia Plant; Christian Böhm 001 (ICDM (Workshops), 2023)

k-SubMix: Common Subspace Clustering on Mixed-Type Data. - Mauritius Klein; Collin Leiber; Christian Böhm 001 (ECML/PKDD (1), 2023)

Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering. - Lena G. M. Bauer; Collin Leiber; Christian Böhm 001; Claudia Plant (SDM, 2023)

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

Dying Clusters Is All You Need - Deep Clustering With an Unknown Number of Clusters. - Collin Leiber; Niklas Strauß; Matthias Schubert; Thomas Seidl 001 (ICDM (Workshops), 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)

Text-Guided Alternative Image Clustering. - Andreas Stephan; Lukas Miklautz; Collin Leiber; Pedro Henrique Luz de Araujo; Dominik Répás; Claudia Plant; Benjamin Roth 001 (CoRR, 2024)

Clustering in transformed feature spaces by analyzing distinct modes. - Collin Leiber (2024)

Breaking the Reclustering Barrier in Centroid-based Deep Clustering. - Lukas Miklautz; Timo Klein; Kevin Sidak; Collin Leiber; Thomas Lang; Andrii Shkabrii; Sebastian Tschiatschek; Claudia Plant (ICLR, 2025)

DCMatch - Identify Matching Architectures in Deep Clustering Through Meta-learning. - Mamdouh Aljoud; Gabriel Marques Tavares; Collin Leiber; Thomas Seidl 001 (PAKDD (1), 2025)

An Introductory Survey to Autoencoder-based Deep Clustering - Sandboxes for Combining Clustering with Deep Learning. - Collin Leiber; Lukas Miklautz; Claudia Plant; Christian Böhm 001 (CoRR, 2025)