| Attitudes, beliefs, and development data concerning agile software development practices C Matthies, J Huegle, T Dürschmid, R Teusner 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | 20 | 2019 |
| Order-independent constraint-based causal structure learning for gaussian distribution models using GPUs C Schmidt, J Huegle, M Uflacker Proceedings of the 30th International Conference on Scientific and …, 2018 | 20 | 2018 |
| Quantitative impact evaluation of an abstraction layer for data stream processing systems G Hesse, C Matthies, K Glass, J Huegle, M Uflacker 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019 | 18 | 2019 |
| GPU-accelerated constraint-based causal structure learning for discrete data C Hagedorn, J Huegle Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 14 | 2021 |
| How Causal Structural Knowledge Adds Decision-Support in Monitoring of Automotive Body Shop Assembly Lines J Huegle, C Hagedorn, M Uflacker | 14 | 2020 |
| GPU acceleration for information-theoretic constraint-based causal discovery C Hagedorn, C Lange, J Huegle, R Schlosser The KDD'22 Workshop on Causal Discovery, 30-60, 2022 | 11 | 2022 |
| Understanding unforeseen production downtimes in manufacturing processes using log data-driven causal reasoning C Hagedorn, J Huegle, R Schlosser Journal of Intelligent Manufacturing 33 (7), 2027-2043, 2022 | 10 | 2022 |
| MPCSL-a modular pipeline for causal structure learning J Huegle, C Hagedorn, M Perscheid, H Plattner Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 8 | 2021 |
| Load-balanced parallel constraint-based causal structure learning on multi-core systems for high-dimensional data C Schmidt, J Huegle, P Bode, M Uflacker The 2019 ACM SIGKDD Workshop on Causal Discovery, 59-77, 2019 | 7 | 2019 |
| MANM-CS: Data Generation for Benchmarking Causal Structure Learning from Mixed Discrete-Continuous and Nonlinear Data J Huegle, C Hagedorn, L Böhme, M Pörschke, J Umland, R Schlosser Proceedings of the 35th Conference on Neural Information Processing Systems …, 2021 | 6 | 2021 |
| An Information-Theoretic Approach on Causal Structure Learning for Heterogeneous Data Characteristics of Real-World Scenarios J Huegle International Joint Conference on Artificial Intelligence, 4891-4892, 2021 | 5 | 2021 |
| Out-of-core GPU-accelerated causal structure learning C Schmidt, J Huegle, S Horschig, M Uflacker Algorithms and Architectures for Parallel Processing: 19th International …, 2020 | 4 | 2020 |
| Constraint-Based Causal Structure Learning in Multi-GPU Environments. C Hagedorn, J Huegle LWDA, 106-118, 2021 | 3 | 2021 |
| Towards a GPU-Accelerated Causal Inference C Schmidt, J Huegle HPI Future SOC Lab: Proceedings 2017 130, 187, 2019 | 2 | 2019 |
| A KNN-Based Non-Parametric Conditional Independence Test for Mixed Data and Application in Causal Discovery J Huegle, C Hagedorn, R Schlosser Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 1 | 2023 |
| GPUCSL: GPU-Based Library for Causal Structure Learning T Braun, B Hurdelhey, D Meier, P Tsayun, C Hagedorn, J Huegle, ... 2022 IEEE International Conference on Data Mining Workshops (ICDMW), 1236-1239, 2022 | 1 | 2022 |
| Unterstützte Fehlerbehebung durch kausales Strukturwissen in Überwachungssystemen der Automobilfertigung. J Huegle, C Hagedorn, M Uflacker Software Engineering (Satellite Events), 2021 | 1 | 2021 |
| Self-learning Agents for Recommerce Markets J Groeneveld, J Herrmann, N Mollenhauer, L Dreeßen, N Bessin, JS Tast, ... Business & Information Systems Engineering, 1-23, 2023 | | 2023 |
| A GPU-Accelerated Skeleton Discovery for Gaussian Distribution Models C Schmidt, J Hügle, S Horschig, M Uflacker HPI Future SOC Lab–Proceedings 2018, 61, 2023 | | 2023 |
| Strategies for an Improved GPU-Accelerated Skeleton Discovery for Gaussian Distribution Models C Schmidt, J Hügle, M Uflacker HPI Future SOC Lab–Proceedings 2018, 187, 2023 | | 2023 |
