| Deep embedded non-redundant clustering L Miklautz, D Mautz, MC Altinigneli, C Böhm, C Plant Proceedings of the AAAI conference on artificial intelligence 34 (04), 5174-5181, 2020 | 22 | 2020 |
| Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces. L Miklautz, LGM Bauer, D Mautz, S Tschiatschek, C Böhm, C Plant IJCAI, 2826-2832, 2021 | 11 | 2021 |
| Deep clustering with consensus representations L Miklautz, M Teuffenbach, P Weber, R Perjuci, W Durani, C Böhm, ... 2022 IEEE International Conference on Data Mining (ICDM), 1119-1124, 2022 | 10 | 2022 |
| Contrastive tuning: A little help to make masked autoencoders forget J Lehner, B Alkin, A Fürst, E Rumetshofer, L Miklautz, S Hochreiter Proceedings of the AAAI Conference on Artificial Intelligence 38 (4), 2965-2973, 2024 | 8 | 2024 |
| Mim-refiner: A contrastive learning boost from intermediate pre-trained representations B Alkin, L Miklautz, S Hochreiter, J Brandstetter arXiv preprint arXiv:2402.10093, 2024 | 6 | 2024 |
| 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 | 5 | 2023 |
| Text-Guided Image Clustering A Stephan, L Miklautz, K Sidak, JP Wahle, B Gipp, C Plant, B Roth Proceedings of the 18th Conference of the European Chapter of the …, 2024 | 3 | 2024 |
| Hierarchical quick shift guided recurrent clustering MC Altinigneli, L Miklautz, C Böhm, C Plant 2020 IEEE 36th international conference on data engineering (ICDE), 1842-1845, 2020 | 3 | 2020 |
| 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 |
| The Data Mining Group at University of Vienna: Clustering, Causality, Massive Data and Applications C Altinigneli, LGM Bauer, S Behzadi, R Fritze, K Hlaváčková-Schindler, ... Datenbank-Spektrum 20, 71-79, 2020 | 1 | 2020 |
| Non-Linear Cluster Enhancement: Forcing Clusters into a Compact Shape. B Schelling, L Miklautz, C Plant ECAI, 1451-1458, 2020 | 1 | 2020 |
| Plasticity Loss in Deep Reinforcement Learning: A Survey T Klein, L Miklautz, K Sidak, C Plant, S Tschiatschek arXiv preprint arXiv:2411.04832, 2024 | | 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 | | 2024 |
| SHADE: Deep Density-based Clustering A Beer, P Weber, L Miklautz, C Leiber, W Durani, C Böhm, C Plant arXiv preprint arXiv:2410.06265, 2024 | | 2024 |
| Prototyp-basiertes Lernen von Repräsentationen mittels Deep Clustering L Miklautz Ausgezeichnete Informatikdissertationen 2023 (Band 24), 181-190, 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 |
| CaFe DBSCAN: A Density-based Clustering Algorithm for Causal Feature Learning P Weber, L Miklautz, A Kumar, M Grosse-Wentrup, C Plant 2023 IEEE 10th International Conference on Data Science and Advanced …, 2023 | | 2023 |
| Tutorial: Application of Deep Clustering Algorithms C Leiber, L Miklautz, C Plant, C Böhm | | |
Claudia PlantProfessor of Computer Science, leader of research group Data Mining and Machine Learning, UniVieEmail verificata su univie.ac.at
