| Analysing cooking behaviour in home settings: Towards health monitoring K Yordanova, S Lüdtke, S Whitehouse, F Krüger, A Paiement, M Mirmehdi, ... Sensors 19 (3), 646, 2019 | 36 | 2019 |
| Context-aware human activity recognition in industrial processes F Niemann, S Lüdtke, C Bartelt, M Ten Hompel Sensors 22 (1), 134, 2021 | 31 | 2021 |
| An algorithm for actigraphy-based sleep/wake scoring: Comparison with polysomnography S Lüdtke, W Hermann, T Kirste, H Beneš, S Teipel Clinical Neurophysiology 132 (1), 137-145, 2021 | 27 | 2021 |
| Combining symbolic reasoning and deep learning for human activity recognition FM Rueda, S Lüdtke, M Schröder, K Yordanova, T Kirste, GA Fink 2019 IEEE International Conference on Pervasive Computing and Communications …, 2019 | 20 | 2019 |
| Explanations for neural networks by neural networks S Marton, S Lüdtke, C Bartelt Applied Sciences 12 (3), 980, 2022 | 18 | 2022 |
| Effect of spatial disorientation in a virtual environment on gait and vital features in patients with dementia: Pilot single-blind randomized control trial CO Amaefule, S Lüdtke, T Kirste, SJ Teipel JMIR Serious Games 8 (4), e18455, 2020 | 15 | 2020 |
| State-space abstractions for probabilistic inference: a systematic review S Lüdtke, M Schröder, F Krüger, S Bader, T Kirste Journal of Artificial Intelligence Research 63, 789-848, 2018 | 15 | 2018 |
| Gradtree: Learning axis-aligned decision trees with gradient descent S Marton, S Lüdtke, C Bartelt, H Stuckenschmidt Proceedings of the AAAI conference on artificial intelligence 38 (13), 14323 …, 2024 | 11 | 2024 |
| GRANDE: Gradient-based decision tree ensembles for tabular data S Marton, S Lüdtke, C Bartelt, H Stuckenschmidt arXiv preprint arXiv:2309.17130, 2023 | 11 | 2023 |
| Online Random Feature Forests for Learning in Varying Feature Spaces C Schreckenberger, Y He, S Lüdtke, C Bartelt, H Stuckenschmidt Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 2023 | 11 | 2023 |
| Lifted filtering via exchangeable decomposition S Lüdtke, M Schröder, S Bader, K Kersting, T Kirste arXiv preprint arXiv:1801.10495, 2018 | 11 | 2018 |
| Mapping glacier basal sliding applying machine learning J Umlauft, CW Johnson, P Roux, DT Trugman, A Lecointre, A Walpersdorf, ... Journal of Geophysical Research: Earth Surface 128 (11), e2023JF007280, 2023 | 5 | 2023 |
| On the Aggregation of Rules for Knowledge Graph Completion P Betz, S Lüdtke, C Meilicke, H Stuckenschmidt Knowledge and Logical Reasoning in the Era of Data-driven Learning (ICML …, 2023 | 5 | 2023 |
| Human activity and context recognition using lifted marginal filtering S Lüdtke, K Yordanova, T Kirste 2019 IEEE International Conference on Pervasive Computing and Communications …, 2019 | 5 | 2019 |
| Approximate probabilistic parallel multiset rewriting using mcmc S Lüdtke, M Schröder, T Kirste KI 2018: Advances in Artificial Intelligence: 41st German Conference on AI …, 2018 | 5 | 2018 |
| Human Activity Recognition using Attribute-Based Neural Networks and Context Information S Lüdtke, FM Rueda, W Ahmed, GA Fink, T Kirste arXiv preprint arXiv:2111.04564, 2021 | 4 | 2021 |
| LiMa: sequential lifted marginal filtering on multiset state descriptions M Schröder, S Lüdtke, S Bader, F Krüger, T Kirste KI 2017: Advances in Artificial Intelligence: 40th Annual German Conference …, 2017 | 4 | 2017 |
| Outlying aspect mining via sum-product networks S Lüdtke, C Bartelt, H Stuckenschmidt Pacific-Asia Conference on Knowledge Discovery and Data Mining, 27-38, 2023 | 3 | 2023 |
| Abstracting from Observation-Equivalent Entities in Human Behavior Modeling. M Schröder, S Lüdtke, S Bader, F Krüger, T Kirste AAAI Workshops, 2017 | 3 | 2017 |
| Explaining neural networks without access to training data S Marton, S Lüdtke, C Bartelt, A Tschalzev, H Stuckenschmidt Machine Learning 113 (6), 3633-3652, 2024 | 2 | 2024 |
Thomas KirsteProfessor für Informatik, Universität RostockEmail được xác minh tại uni-rostock.de
