Stefan Lüdtke

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 44

Top Topics

Decision Tree Ensembles

Activity Recognition

Industrial Process

Machine Learning Models

Top Venues

PerCom Workshops

Publications

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt
Explaining neural networks without access to training data. Mach. Learn. 113 (6) (2024)
Andrej Tschalzev, Paul Nitschke, Lukas Kirchdorfer, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods. CoRR (2024)
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent. AAAI (2024)
Andrej Tschalzev, Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data. CoRR (2024)
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data. ICLR (2024)
Christian Schreckenberger, Yi He, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Online Random Feature Forests for Learning in Varying Feature Spaces. AAAI (2023)
Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Outlying Aspect Mining via Sum-Product Networks. PAKDD (1) (2023)
Patrick Betz, Stefan Lüdtke, Christian Meilicke, Heiner Stuckenschmidt
On the Aggregation of Rules for Knowledge Graph Completion. CoRR (2023)
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
GRANDE: Gradient-Based Decision Tree Ensembles. CoRR (2023)
Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Leveraging Planning Landmarks for Hybrid Online Goal Recognition. CoRR (2023)
Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Heiner Stuckenschmidt
Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition. CoRR (2023)
Stefan Lüdtke, Maria E. Pierce
Towards Machine Learning-based Fish Stock Assessment. CoRR (2023)
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Learning Decision Trees with Gradient Descent. CoRR (2023)
Maximilian Popko, Sebastian Bader, Stefan Lüdtke, Thomas Kirste
Discovering Behavioural Predispositions in Data to Improve Human Activity Recognition. iWOAR (2022)
Maximilian Popko, Sebastian Bader, Stefan Lüdtke, Thomas Kirste
Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition. CoRR (2022)
Friedrich Niemann, Stefan Lüdtke, Christian Bartelt, Michael ten Hompel
Context-Aware Human Activity Recognition in Industrial Processes. Sensors 22 (1) (2022)
Timon Felske, Stefan Lüdtke, Sebastian Bader, Thomas Kirste
Activity Recognition in Assembly Tasks by Bayesian Filtering in Multi-Hypergraphs. CoRR (2022)
Michael Oesterle, Christian Bartelt, Stefan Lüdtke, Heiner Stuckenschmidt
Self-learning Governance of Black-Box Multi-Agent Systems. COINE (2022)
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt
Explaining Neural Networks without Access to Training Data. CoRR (2022)
Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Outlier Explanation via Sum-Product Networks. CoRR (2022)
Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Exchangeability-Aware Sum-Product Networks. IJCAI (2022)
Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
Exchangeability-Aware Sum-Product Networks. CoRR (2021)
Stefan Lüdtke, Fernando Moya Rueda, Waqas Ahmed, Gernot A. Fink, Thomas Kirste
Human Activity Recognition using Attribute-Based Neural Networks and Context Information. CoRR (2021)
Stefan Lüdtke, Thomas Kirste
Lifted Bayesian Filtering in Multiset Rewriting Systems. J. Artif. Intell. Res. 69 (2020)
Stefan Lüdtke, Chimezie O. Amaefule, Thomas Kirste, Stefan J. Teipel
Measuring motion behavior to detect spatial disorientation in a VR environment. PETRA (2020)
Stefan Lüdtke, Marcel Gehrke, Tanya Braun, Ralf Möller, Thomas Kirste
Lifted Marginal Filtering for Asymmetric Models by Clustering-Based Merging. ECAI (2020)
Kristina Y. Yordanova, Stefan Lüdtke, Samuel Whitehouse, Frank Krüger, Adeline Paiement, Majid Mirmehdi, Ian Craddock, Thomas Kirste
Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring. Sensors 19 (3) (2019)
Stefan Lüdtke, Maximilian Popko, Thomas Kirste
On the Applicability of Probabilistic Programming Languages for Causal Activity Recognition. Künstliche Intell. 33 (4) (2019)
Fernando Moya Rueda, Stefan Lüdtke, Max Schröder, Kristina Y. Yordanova, Thomas Kirste, Gernot A. Fink
Combining Symbolic Reasoning and Deep Learning for Human Activity Recognition. PerCom Workshops (2019)
Stefan Lüdtke, Kristina Y. Yordanova, Thomas Kirste
Human Activity and Context Recognition using Lifted Marginal Filtering. PerCom Workshops (2019)
Stefan Lüdtke, Alejandro Molina, Kristian Kersting, Thomas Kirste
Gaussian Lifted Marginal Filtering. KI (2019)
Stefan Lüdtke, Max Schröder, Thomas Kirste
Approximate Probabilistic Parallel Multiset Rewriting Using MCMC. KI (2018)
Samuel Whitehouse, Kristina Y. Yordanova, Stefan Lüdtke, Adeline Paiement, Majid Mirmehdi
Evaluation of cupboard door sensors for improving activity recognition in the kitchen. PerCom Workshops (2018)
Kai Schröter, Stefan Lüdtke, Richard Redweik, Jessica Meier, Mathias Bochow, Lutz Ross, Claus Nagel, Heidi Kreibich
Flood loss estimation using 3D city models and remote sensing data. Environ. Model. Softw. 105 (2018)
Stefan Lüdtke, Max Schröder, Sebastian Bader, Kristian Kersting, Thomas Kirste
Lifted Filtering via Exchangeable Decomposition. IJCAI (2018)
Stefan Lüdtke, Max Schröder, Sebastian Bader, Kristian Kersting, Thomas Kirste
Lifted Filtering via Exchangeable Decomposition. CoRR (2018)
Stefan Lüdtke, Max Schröder, Frank Krüger, Sebastian Bader, Thomas Kirste
State-Space Abstractions for Probabilistic Inference: A Systematic Review. J. Artif. Intell. Res. 63 (2018)
Stefan Lüdtke, Alejandro Molina, Thomas Kirste
Gaussian Lifted Marginal Filtering. iWOAR (2018)
Stefan Lüdtke, Max Schröder, Frank Krüger, Sebastian Bader, Thomas Kirste
State-Space Abstractions for Probabilistic Inference: A Systematic Review. CoRR (2018)
Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste
Abstracting from Observation-Equivalent Entities in Human Behavior Modeling. AAAI Workshops (2017)
Stefan Lüdtke, Max Schröder, Frank Krüger, Thomas Kirste
Where are my colleagues?: Tracking and Counting Multiple Persons using Lifted Marginal Filtering. iWOAR (2017)
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. BIOSIGNALS (2017)
Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste
Sequential Lifted Bayesian Filtering in Multiset Rewriting Systems. CoRR (2017)
Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste
LiMa: Sequential Lifted Marginal Filtering on Multiset State Descriptions. KI (2017)
Stefan Lüdtke, Benjamin Wagner, Ralf Bruder, Patrick Stüber, Floris Ernst, Achim Schweikard, Tobias Wissel
Calibration of Galvanometric Laser Scanners Using Statistical Learning Methods. Bildverarbeitung für die Medizin (2015)