A case for hardware-supported sub-cache line accesses. - Christopher Schmidt 001; Markus Dreseler; Berkin Akin; Amithaba Roy (DaMoN, 2018)

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

Workload-Driven Data Placement for GPU-Accelerated Database Management Systems. - Christopher Schmidt 001; Matthias Uflacker (BTW (Workshops), 2019)

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

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)

Parallel execution of causal structure learning on graphics processing units. - Christopher Hagedorn (2023)