Gesture based robot programming using process knowledge - An example for welding applications. - Oliver Heimann; Johannes Hügle; Jörg Krüger (ETFA, 2017)

An integrated approach for industrial robot control and programming combining haptic and non-haptic gestures. - Johannes Hügle; Jens Lambrecht; Jörg Krüger (RO-MAN, 2017)

Order-independent constraint-based causal structure learning for gaussian distribution models using GPUs. - Christopher Schmidt 001; Johannes Huegle; Matthias Uflacker (SSDBM, 2018)

Combining the Advantages of On- and Offline Industrial Robot Programming. - Jan Guhl; Sylvio Nikoleizig; Oliver Heimann; Johannes Hügle; Jörg Krüger (ETFA, 2019)

An automatic calibration approach for a multi-camera-robot system. - Ole Kröger; Johannes Huegle; Carsten A. Niebuhr (ETFA, 2019)

Out-of-Core GPU-Accelerated Causal Structure Learning. - Christopher Schmidt 001; Johannes Huegle; Siegfried Horschig; Matthias Uflacker (ICA3PP (1), 2019)

Quantitative Impact Evaluation of an Abstraction Layer for Data Stream Processing Systems. - Guenter Hesse; Christoph Matthies; Kelvin Glass; Johannes Huegle; Matthias Uflacker (ICDCS, 2019)

Load-Balanced Parallel Constraint-Based Causal Structure Learning on Multi-Core Systems for High-Dimensional Data. - Christopher Schmidt 001; Johannes Huegle; Philipp Bode; Matthias Uflacker (CD@KDD, 2019)

How Causal Structural Knowledge Adds Decision-Support in Monitoring of Automotive Body Shop Assembly Lines. - Johannes Huegle; Christopher Hagedorn; Matthias Uflacker (IJCAI, 2020)

Attitudes, Beliefs, and Development Data Concerning Agile Software Development Practices. - Christoph Matthies; Johannes Huegle; Tobias Dürschmid; Ralf Teusner (SE, 2020)

An Information-Theoretic Approach on Causal Structure Learning for Heterogeneous Data Characteristics of Real-World Scenarios. - Johannes Huegle (IJCAI, 2021)

MPCSL - A Modular Pipeline for Causal Structure Learning. - Johannes Huegle; Christopher Hagedorn; Michael Perscheid; Hasso Plattner (KDD, 2021)

Constraint-Based Causal Structure Learning in Multi-GPU Environments. - Christopher Hagedorn; Johannes Huegle (LWDA, 2021)

GPU-Accelerated Constraint-Based Causal Structure Learning for Discrete Data. - Christopher Hagedorn; Johannes Huegle (SDM, 2021)

Unterstützte Fehlerbehebung durch kausales Strukturwissen in Überwachungssystemen der Automobilfertigung. - Johannes Huegle; Christopher Hagedorn; Matthias Uflacker (Software Engineering (Satellite Events), 2021)

GPUCSL: GPU-Based Library for Causal Structure Learning. - Tom Braun; Ben Hurdelhey; Dominik Meier; Petr Tsayun; Christopher Hagedorn; Johannes Huegle; Rainer Schlosser (ICDM (Workshops), 2022)

GPU Acceleration for Information-theoretic Constraint-based Causal Discovery. - Christopher Hagedorn; Constantin Lange; Johannes Huegle; Rainer Schlosser (CD@KDD, 2022)

Understanding unforeseen production downtimes in manufacturing processes using log data-driven causal reasoning. - Christopher Hagedorn; Johannes Huegle; Rainer Schlosser (J. Intell. Manuf., 2022)

A KNN-Based Non-Parametric Conditional Independence Test for Mixed Data and Application in Causal Discovery. - Johannes Huegle; Christopher Hagedorn; Rainer Schlosser (ECML/PKDD (1), 2023)

Causal discovery in practice: Non-parametric conditional independence testing and tooling for causal discovery (Kausale Entdeckung in der Praxis: Nichtparametrische bedingte Unabhängigkeitstests und Werkzeuge für die Kausalentdeckung) - Johannes Huegle (2024)

Self-learning Agents for Recommerce Markets. - Jan Groeneveld; Judith Herrmann; Nikkel Mollenhauer; Leonard Dreeßen; Nick Bessin; Johann Schulze Tast; Alexander Kastius; Johannes Huegle; Rainer Schlosser (Bus. Inf. Syst. Eng., 2024)