2024

  • Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. GRANDE: Gradient-Based Decision Tree Ensembles. International Conference on Learning Representations (ICLR) 2024.

  • Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent. Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI) 2024.

  • Sascha Marton, Stefan Lüdtke , Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt. Explaining Neural Networks without Access to Training Data. Springer Machine Learning. 2024. [web]

2023

  • Josefine Umlauft, Christopher W Johnson, Philippe Roux, Daniel Taylor Trugman, Albanne Lecointre, Andrea Walpersdorf, Ugo Nanni, Florent Gimbert, Bertrand Rouet‐Leduc, Claudia Hulbert, Stefan Lüdtke, Sascha Marton, Paul A Johnson. Mapping glacier basal sliding applying machine learning. Journal of Geophysical Research: Earth Surface 128.11. 2023. [web]

  • Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent. NeurIPS 2023 Second Table Representation Learning Workshop. 2023. [web]

  • Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. GRANDE: Gradient-Based Decision Tree Ensembles. arXiv preprint arXiv:2309.17130. 2023. [web]

  • Stefan Lüdtke, Maria E. Pierce. Towards Machine Learning-based Fish Stock Assessment. Fragile Earth: AI for Climate Sustainability - from Wildfire Disaster Management to Public Health and Beyond (KDD Workshop) 2023. [web]

  • Patrick Betz, Stefan Lüdtke, Christian Meilicke, Heiner Stuckenschmidt. On the aggregation of rules for knowledge graph completion. Knowledge and Logical Reasoning in the Era of Data-driven Learning (ICML Workshop) 2023. [web]

  • Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent. arXiv preprint arXiv:2305.03515. 2023. [web]

  • Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Heiner Stuckenschmidt. Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition. arXiv preprint arXiv:2301.05608. 2023. [web]

  • Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. Leveraging Planning Landmarks for Hybrid Online Goal Recognition. arXiv preprint arXiv:2301.10571. 2023. [web]

  • Christian Schreckenberger, Yi He, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. Online random feature forests for learning in varying feature spaces. Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) 2023.

  • Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. Outlying Aspect Mining via Sum-Product Networks. Proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2023. [web]

  • Chimezie O. Amaefule, Stefan Lüdtke, Anne Klostermann, Charlotte A. Hinz, Isabell Kampa, Thomas Kirste, Stefan Teipel. At Crossroads in a Virtual City: Effect of Spatial Disorientation on Gait Variability and Psychophysiological Response among Healthy Older Adults. Gerontology 2023. [web]

    2022

  • Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. Exchangeability-Aware Sum-Product Networks. Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI) 2022. [web]

  • Michael Oesterle, Christian Bartelt, Stefan Lüdtke, Heiner Stuckenschmidt. Self-Learning Governance of Black-Box Multi-Agent Systems. Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XV (COINE) 2022. [web]

  • Maximilian Popko, Sebastian Bader, Stefan Lüdtke , Thomas Kirste. Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition. Proceedings of the 7th International Workshop on Sensor-Based Activity Recognition and Artificial Intelligence (iWOAR) 2022. [ACM] [arXiv]

  • Sascha Marton, Stefan Lüdtke , Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt. Explaining Neural Networks without Access to Training Data. arXiv preprint arXiv:2206.04891. 2022. [web]

  • Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt. Leveraging planning landmarks for hybrid online goal recognition. Scheduling and Planning Applications woRKshop (spark) 2022. [web]

  • Stefan Teipel, Chimezie Amaefule, Stefan Lüdtke, Doreen Görß, Sofia Faraza, Sven Bruhn, Thomas Kirste. Prediction of Disorientation by Accelerometric and Gait Features in Young and Older Adults Navigating in a Virtually Enriched Environment. Frontiers in Psychology 2022. [web]

  • Sascha Marton, Stefan Lüdtke, Christian Bartelt. Explanations for neural networks by neural networks. Applied Sciences 2022. [web]

  • Friedrich Niemann, Stefan Lüdtke, Christian Bartelt, Michael ten Hompel. Context-aware human activity recognition in industrial processes. Sensors 2022. [web]

  • Timon Felske, Stefan Lüdtke, Sebastian Bader, Thomas Kirste. Activity Recognition in Assembly Tasks by Bayesian Filtering in Multi-Hypergraphs. 2nd Workshop on Graphs and More Complex Structures for Learning and Reasoning 2022. [web]

  • Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Gait changes among older adults during a virtual wayfinding task: The role of spatial disorientation and heart rate variability. Alzheimer's & Dementia 2022. [web]

    2021

  • Stefan Lüdtke, Fernando Moya Rueda, Waqas Ahmed, Gernot A. Fink, Thomas Kirste. Human Activity Recognition using Attribute-Based Neural Networks and Context Information. 3rd International Workshop on Deep Learning for Human Activity Recognition 2021. [pdf]

  • Stefan Lüdtke. Lifted Bayesian Filtering in Multi-Entity Systems. PhD thesis. 2021. [web]

  • Iris Hochgraeber, Christiane Pinkert, Sumaiya Suravee, Stefan Lüdtke, Margareta Halek, Bernhard Holle. Wissenschaftsbasierte Ontologieentwicklung als Grundlage für KI-basierte Beratung von pflegenden Angehörigen. Einblicke in das Projekt eDEM-CONNECT. 20. deutscher Kongress für Versorgungsforschung 2021.

  • Stefan Lüdtke, Wiebke Hermann, Thomas Kirste, Heike Benes, Stefan Teipel. An Algorithm for Actigraphy-based Sleep/Wake Scoring: Comparison with Polysomnography. Clinical Neurophysiology 2021. [web]

    2020

  • Stefan Lüdtke, Marcel Gehrke, Tanya Braun, Ralf Möller, Thomas Kirste. Lifted Marginal Filtering for Asymmetric Models by Clustering-based Merging. Proceedings of the 24th European Conference on Artificial Intelligence (ECAI) 2020. [pdf]

  • Anne Klostermann, Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Physiological and Gait Pattern Effects of Induced Disorientation in a 3D Virtual Environment. Alzheimer's Association International Conference (AAIC) 2020.

  • Charlotte Hinz, Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Assessing accelerometric, gait and physiological parameters of induced spatial orientation in people with MCI or mild dementia and older healthy cohorts. Alzheimer's Association International Conference (AAIC) 2020. [web]

  • Stefan Lüdtke, Thomas Kirste. Lifted Bayesian Filtering in Multiset Rewriting Systems. Journal of Artificial Intelligence Research (JAIR) 2020. [web]

  • Chimezie Amaefule, Stefan Lüdtke, Thomas Kirste, Stefan Teipel. Effect of Spatial Disorientation in a Virtual Environment on Gait and Vital Features in Patients with Dementia: Pilot Single-Blind Randomized Control Trial. JMIR Serious Games 2020. [web]

  • Stefan Lüdtke, Chimezie Amaefule, Thomas Kirste, Stefan Teipel. Measuring Motion Behavior to Detect Spatial Disorientation in a VR Environment. In The 13th PErvasive Technologies Related to Assistive Environments Conference (PETRA) 2020.

    2019

  • Stefan Lüdtke, Kristina Yordanova, Thomas Kirste. Human Activity and Context Recognition using Lifted Marginal Filtering. Proceedings of the 15th Workshop on Context Modeling and Recognition (CoMoRea) 2019. [pdf]

  • Stefan Lüdtke, Alejandro Molina, Kristian Kersting, Thomas Kirste. Gaussian Lifted Marginal Filtering. KI: Advances in Artificial Intelligence 2019. [pdf]

  • Fernando Moya Rueda, Stefan Lüdtke, Max Schröder, Kristina Yordanova, Thomas Kirste, Gernot Fink. Combining Symbolic Reasoning and Deep Learning for Human Activity Recognition. Proceedings of the 15th Workshop on Context Modeling and Recognition (CoMoRea) 2019. [pdf]

  • Stefan Lüdtke, Maximilian Popko, Thomas Kirste. On the Applicability of Probabilistic Programming Languages for Causal Activity Recognition. German Journal of Artificial Intelligence (Künstliche Intelligenz) 2019. [pdf]

  • Kristina Yordanova, Stefan Lüdtke, Sam Whitehouse, Frank Krüger, Adeline Paiement, Majid Mirmehdi, Ian Craddock, Thomas Kirste. Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring. Sensors 2019.

  • Sarah Weschke, Stefan Lüdtke, Martin Gube, Matthias Weippert, Chimezie Amaefule, Sven Bruhn, Rainer Bader, Thomas Kirste, Stefan Teipel. Measuring Gait Characteristics of Induced Disorientation in a VR Environment. 11. Kongress der Deutschen Gesellschaft für Biomechanik (DGfB) 2019.

  • Chimezie Amaefule, Stefan Lüdtke, Sarah Weschke, Christoph Berger, Sven Bruhn, Rainer Bader, Thomas Kirste, Stefan Teipel. Assessing Gait and Physiological Characteristics of Induced Disorientation in a VR Environment - The journey so far. Deutsche Gesellschaft für Psychiatrie und Psychotherapie, Psychosomatik und Nervenheilkunde (DGPPN) Kongress 2019.

    2018

  • Stefan Lüdtke, Max Schröder, Sebastian Bader, Kristian Kersting, Thomas Kirste. Lifted Filtering via Exchangeable Decomposition. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI) 2018. [pdf]

  • Stefan Lüdtke, Max Schröder, Frank Krüger, Sebastian Bader, Thomas Kirste. State-Space Abstractions for Probabilistic Inference: A Systematic Review. Journal of Artificial Intelligence Research (JAIR) 2018. [pdf]

  • Stefan Lüdtke, Max Schröder, Thomas Kirste. Approximate Probabilistic Parallel Multiset Rewriting using MCMC. KI: Advances in Artificial Intelligence 2018. [pdf]

  • Sam Whitehouse, Kristina Yordanova, Stefan Lüdtke, Adeline Paiement, Majid Mirmehdi. Evaluation of cupboard door sensors for improving activity recognition in the kitchen. PerCom Workshops Proceedings (PerHealth) 2018. [pdf]

    2017

  • Stefan Lüdtke, Max Schröder, Frank Krüger, Thomas Kirste. Where are my colleagues? Tracking and Counting Multiple Persons using Lifted Marginal Filtering. Procedings of the 4th international Workshop on Sensor-based Activity Recognition and Interaction (iWOAR) 2017. [pdf]

  • Stefan Lüdtke, Albert Hein, Frank Krüger, Sebastian Bader, Thomas Kirste. Actigraphic Sleep Detection for Real-World Data of Healthy Young Adults and People with Alzheimer’s Disease. Proceedings of BIOSIGNALS 2017 (BIOSIGNALS) 2017. [pdf]

  • Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste. Abstracting from Observation-equivalent Entities in Human Behavior Modeling. AAAI Workshop: Plan, Activity, and Intent Recognition (PAIR) 2017. [pdf]

  • Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste. Sequential Lifted Bayesian Filtering in Multiset Rewriting Systems. UAI Workshop: Statistical Relational Artificial Intelligence (StarAI) 2017. [pdf]

  • Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste. LiMa: Sequential Lifted Marginal Filtering on Multiset State Descriptions. KI: Advances in Artificial Intelligence 2017. [pdf]