| Dip-based Deep Embedded Clustering with k-Estimation C Leiber, LGM Bauer, B Schelling, C Böhm, C Plant Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 38 | 2021 |
| Benchmarking deep clustering algorithms with clustpy C Leiber, L Miklautz, C Plant, C Böhm 2023 IEEE International Conference on Data Mining Workshops (ICDMW), 625-632, 2023 | 20 | 2023 |
| The dipencoder: Enforcing multimodality in autoencoders C Leiber, LGM Bauer, M Neumayr, C Plant, C Böhm Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 17 | 2022 |
| Extension of the Dip-test Repertoire-Efficient and Differentiable p-value Calculation for Clustering LGM Bauer, C Leiber, C Böhm, C Plant Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 8 | 2023 |
| Data with density-based clusters: A generator for systematic evaluation of clustering algorithms P Jahn, CMM Frey, A Beer, C Leiber, T Seidl Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | 6 | 2024 |
| Shade: Deep density-based clustering A Beer, P Weber, L Miklautz, C Leiber, W Durani, C Böhm, C Plant 2024 IEEE International Conference on Data Mining (ICDM), 675-680, 2024 | 4 | 2024 |
| Breaking the reclustering barrier in centroid-based deep clustering L Miklautz, T Klein, K Sidak, C Leiber, T Lang, A Shkabrii, S Tschiatschek, ... arXiv preprint arXiv:2411.02275, 2024 | 4 | 2024 |
| An Introductory Survey to Autoencoder-based Deep Clustering--Sandboxes for Combining Clustering with Deep Learning C Leiber, L Miklautz, C Plant, C Böhm arXiv preprint arXiv:2504.02087, 2025 | 2 | 2025 |
| Non-redundant image clustering of early medieval glass beads L Miklautz, A Shkabrii, C Leiber, B Tobias, B Seidl, E Weissensteiner, ... 2023 IEEE 10th International Conference on Data Science and Advanced …, 2023 | 2 | 2023 |
| Automatic parameter selection for non-redundant clustering C Leiber, D Mautz, C Plant, C Böhm Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 2 | 2022 |
| DCMatch-Identify Matching Architectures in Deep Clustering Through Meta-learning M Aljoud, GM Tavares, C Leiber, T Seidl Pacific-Asia Conference on Knowledge Discovery and Data Mining, 213-224, 2025 | 1 | 2025 |
| Dying Clusters Is All You Need-Deep Clustering With an Unknown Number of Clusters C Leiber, N Strauß, M Schubert, T Seidl 2024 IEEE International Conference on Data Mining Workshops (ICDMW), 726-733, 2024 | 1 | 2024 |
| DCMatchBoosted-Improving Deep Clustering by Architecture Recommendation M Aljoud, GM Tavares, C Leiber, T Seidl | | 2025 |
| Clustering energy performance certificates: a methodology for selecting representative buildings in scalable energy simulations H Hajian, C Leiber, K Härkönen, H Mannila, A Ferrantelli Energy and Buildings, 116592, 2025 | | 2025 |
| Going Offline: An Evaluation of the Offline Phase in Stream Clustering P Jahn, W Durani, C Leiber, A Beer, T Seidl Joint European Conference on Machine Learning and Knowledge Discovery in …, 2025 | | 2025 |
| Text-Guided Alternative Image Clustering A Stephan, L Miklautz, C Leiber, PHL De Araujo, D Repas, C Plant, ... arXiv preprint arXiv:2406.18589, 2024 | | 2024 |
| Clustering in transformed feature spaces by analyzing distinct modes C Leiber lmu, 2024 | | 2024 |
| Application of Deep Clustering Algorithms C Leiber, L Miklautz, C Plant, C Böhm Proceedings of the 32nd ACM International Conference on Information and …, 2023 | | 2023 |
| k-SubMix: Common Subspace Clustering on Mixed-Type Data M Klein, C Leiber, C Böhm Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | | 2023 |
| Supplement-’Automatic Parameter Selection for Non-Redundant Clustering’ C Leiber, D Mautz, C Plant, C Böhm | | 2022 |
Claudia PlantProfessor of Computer Science, leader of research group Data Mining and Machine Learning, UniVieVerified email at univie.ac.at
