Publikationen

2024[ to top ]
  • Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction. Huang, Zhixin; He, Yujiang; Nivarthi, Chandana Priya; Gruhl, Christian; Sick, Bernhard. In International Conference on Pattern Recognition (ICPR), bll 1–21. Springer, 2024.
  • Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction. Huang, Zhixin; Nivarthi, Chandana Priya; Gruhl, Christian; Sick, Bernhard. In International Joint Conference on Neural Networks (IJCNN), bll 1–9. IEEE, 2024.
  • Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection. Nivarthi, Chandana Priya; Huang, Zhixin; Gruhl, Christian; Sick, Bernhard. In International Joint Conference on Neural Networks (IJCNN), bll 1–10. IEEE, 2024.
  • LiST: An All-Linear-Layer Spatial-Temporal Feature Extractor with Uncertainty Estimation for RUL Prediction. Huang, Zhixin; Gruhl, Christian; Sick, Bernhard. In IEEE Conference on Industrial Electronics and Applications (ICIEA), bll 1–7. IEEE, 2024.
  • From Structured to Unstructured: A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs. Decke, Jens; Wünsch, Olaf; Sick, Bernhard; Gruhl, Christian. In International Conference on Architecture of Computing Systems (ARCS), bll 82–96. Springer, 2024.
  • An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing. Decke, Jens; Jenß, Arne; Sick, Bernhard; Gruhl, Christian. In International Conference on Architecture of Computing Systems (ARCS), bll 51–66. Springer, 2024.
2023[ to top ]
  • Self-Integration and Agent Compatibility. Gruhl, Christian; Sick, Bernhard. In Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), bll 71–73. IEEE, 2023.
  • Self-awareness in Cyber-Physical Systems: Recent Developments and Open Challenges. Esterle, Lukas; Dutt, Nikil; Gruhl, Christian; Lewis, Peter R.; Marcenaro, Lucio; Regazzoni, Carlo; Jantsch, Axel. In Design, Automation & Test in Europe Conference & Exhibition (DATE), bll 1–6. IEEE, 2023.
  • DADO – Low-Cost Query Strategies for Deep Active Design Optimization. Decke, Jens; Gruhl, Christian; Rauch, Lukas; Sick, Bernhard. In International Conference on Machine Learning and Applications (ICMLA), bll 1611–1618. IEEE, 2023.
2022[ to top ]
  • The Vision of Self-Management in Cognitive Organic Power Distribution Systems. Loeser, Inga; Braun, Martin; Gruhl, Christian; Menke, Jan-Hendrik; Sick, Bernhard; Tomforde, Sven. In Energies, 15(3), bl 881. MDPI, 2022.
  • Social Machines. Draude, Claude; Gruhl, Christian; Hornung, Gerrit; Kropf, Jonathan; Lamla, Jörn; Leimeister, Jan Marco; Sick, Bernhard; Stumme, Gerd. In Informatik Spektrum, 45(1), bll 38–42. Springer, 2022.
  • Self-Aware Microsystems. Gruhl, Christian; Tomforde, Sven; Sick, Bernhard. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 126–127. IEEE, 2022.
  • Proactive hybrid learning and optimisation in self-adaptive systems: The swarm-fleet infrastructure scenario. Krupitzer, Christian; Gruhl, Christian; Sick, Bernhard; Tomforde, Sven. In Information and Software Technology, 145, bl 106826. Elsevier, 2022.
  • NDNET: A Unified Framework for Anomaly and Novelty Detection. Decke, Jens; Schmeißing, Jörn; Botache, Diego; Bieshaar, Maarten; Sick, Bernhard; Gruhl, Christian. In International Conference on Architecture of Computing Systems (ARCS), bll 197–210. Springer, 2022.
2021[ to top ]
  • The Problem with Real-World Novelty Detection -- Issues in Multivariate Probabilistic Models. Gruhl, Christian; Hannan, Abdul; Huang, Zhixin; Nivarthi, Chandana; Vogt, Stephan. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 204–209. IEEE, 2021.
  • Self-improving system integration: Mastering continuous change. Bellman, Kirstie; Botev, Jean; Diaconescu, Ada; Esterle, Lukas; Gruhl, Christian; Landauer, Christopher; Lewis, Peter R.; Nelson, Phyllis R.; Pournaras, Evangelos; Stein, Anthony; Tomforde, Sven. In Future Generation Computer Systems, 117, bll 29–46. Elsevier, 2021.
  • OHODIN -- Online Anomaly Detection for Data Streams. Gruhl, Christian; Tomforde, Sven. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 193–197. IEEE, 2021.
  • Novelty detection in continuously changing environments. Gruhl, Christian; Sick, Bernhard; Tomforde, Sven. In Future Generation Computer Systems, 114, bll 138–154. Elsevier, 2021.
  • Novelty based Driver Identification on RR Intervals from ECG Data. Heidecker, Florian; Gruhl, Christian; Sick, Bernhard. In Workshop on Integrated Artificial Intelligence in Data Science, ICPR, bll 407–421. IEEE, Milan, Italy, 2021.
  • Digital Shadows in Self-Improving System Integration: A Concept Using Generative Modelling. Al-Falouji, Ghassan; Gruhl, Christian; Tomforde, Sven. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 166–171. IEEE, 2021.
  • Anomaly based Resilient Network Intrusion Detection using Inferential Autoencoders. Hannan, Abdul; Gruhl, Christian; Sick, Bernhard. In IEEE International Conference on Cyber Security and Resilience (CSR), bll 1–7. IEEE, 2021.
2020[ to top ]
  • Normal-Wishart clustering for novelty detection. Gruhl, Christian; Schmeißing, Jörn; Tomforde, Sven; Sick, Bernhard. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 64–69. IEEE, 2020.
  • Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. Pham Minh, T.; Kottke, D.; Tsarenko, A.; Gruhl, C.; Sick, B. In International Joint Conference on Neural Networks (IJCNN). IEEE, 2020.
  • Fairness, performance, and robustness: is there a cap theorem for self-adaptive and self-organising systems?. Tomforde, Sven; Gruhl, Christian. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 54–59. IEEE, 2020.
  • A swarm-fleet infrastructure as a scenario for proactive, hybrid adaptation of system behaviour. Tomforde, Sven; Gruhl, Christian; Sick, Bernhard. In Workshop on Self -Aware Computing (SeAC), ACSOS, bll 166–169. IEEE, 2020.
2019[ to top ]
  • Self-Improving System Integration -- On a Definition and Characteristics of the Challenge. Bellman, K. L.; Gruhl, C.; Landauer, C.; Tomforde, S. In Workshop on Self-Improving System Integration (SISSY), FAS*W, bll 1–3. IEEE, 2019.
  • Explicit Consideration of Resilience in Organic Computing Design Processes. Tomforde, S.; Gelhausen, P.; Gruhl, C.; Haering, I.; Sick, B. In International Workshop on Self-optimisation in Organic and Autonomic Computing Systems (SAOS), ARCS, bll 1–6. VDE, 2019.
  • CHARIOT -- Towards a Continuous High-Level Adaptive Runtime Integration Testbed. Barnes, C. M.; Bellman, K.; Botev, J.; Diaconescu, A.; Esterle, L.; Gruhl, C.; Landauer, C.; Lewis, P. R.; Nelson, P. R.; Stein, A.; Stewart, C.; Tomforde, S. In Workshop on Self-Improving System Integration (SISSY), FAS*W, bll 52–55. IEEE, 2019.
2018[ to top ]
  • Novelty detection with CANDIES: a holistic technique based on probabilistic models. Gruhl, Christian; Sick, Bernhard. In International Journal of Machine Learning and Cybernetics, 9(6), bll 927–945. Springer, 2018.
  • Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. Gruhl, Christian; Tomforde, Sven; Sick, Bernhard. In Workshop on Self-Improving System Integration (SISSY), FAS*W, bll 198–203. IEEE, 2018.
2017[ to top ]
  • Highly Autonomous Learning in Collaborative, Technical Systems. Gruhl, C. In Organic Computing -- Doctoral Dissertation Colloquium 2017, S. Tomforde, B. Sick (reds.). kassel university press, Kassel, Germany, 2017.
  • A Concept for Intelligent Collaborative Network Intrusion Detection. Gruhl, C.; Beer, F.; Heck, H.; Sick, B.; Bühler, U.; Wacker, A.; Tomforde, S. In International Workshop on Self-optimisation in Organic and Autonomic Computing Systems (SAOS), ARCS. VDE, 2017.
2016[ to top ]
  • Towards Autonomous Self-tests at Runtime. Heck, H.; Wacker, A.; Rudolph, S.; Gruhl, C.; Sick, B.; Tomforde, S. In IEEE International Workshop on Quality Assurance for Self-Adaptive, Self-Organising Systems (QA4SASO), FAS*W, bll 98–99. IEEE, 2016.
  • Towards Automation of Knowledge Understanding: An Approach for Probabilistic Generative Classifiers. Fisch, D.; Gruhl, C.; Kalkowski, E.; Sick, B.; Ovaska, S. J. In Information Sciences, 370--371, bll 476–496. Elsevier, 2016.
  • Probabilistic Obsoleteness Detection for Gaussian Mixture Models. Gruhl, C. In Organic Computing -- Doctoral Dissertation Colloquium 2016, S. Tomforde, B. Sick (reds.), bll 45–56. kassel university press, Kassel, Germany, 2016.
  • Multi-k-Resilience in Distributed Adaptive Cyber-Physical Systems. Heck, H.; Gruhl, C.; Rudolph, S.; Wacker, A.; Sick, B.; Hähner, J. In International Workshop on Self-optimisation in Organic and Autonomic Computing Systems (SAOS), ARCS, bll 1–8. VDE, Nuremberg, Germany, 2016.
2015[ to top ]
  • On the Application Possibilities of Organic Computing Principles in Socio-technical Systems. Heck, H.; Edenhofer, S.; Gruhl, C.; Lund, A.; Shuka, R.; Hähner, J. In Organic Computing -- Doctoral Dissertation Colloquium 2015, S. Tomforde, B. Sick (reds.), bll 165–170. kassel university press, Kassel, Germany, 2015.
  • Anomalies in Generative Trajectory Models -- Discovering Suspicious Traces with Novelty Detection Methods. Gruhl, C. In Organic Computing -- Doctoral Dissertation Colloquium 2015, S. Tomforde, B. Sick (reds.), bll 95–107. kassel university press, Kassel, Germany, 2015.
  • A building block for awareness in technical systems: Online novelty detection and reaction with an application in intrusion detection. Gruhl, C.; Sick, B.; Wacker, A.; Tomforde, S.; Hähner, J. In IEEE International Conference on Awareness Science and Technology (iCAST), bll 194–200. IEEE, Qinhuangdao, China, 2015.
2014[ to top ]
  • Self-Adapting Generative Modeling Techniques -- A Basic Building Block for Many Organic Computing Techniques. Gruhl, C. In Organic Computing -- Doctoral Dissertation Colloquium 2014, S. Tomforde, B. Sick (reds.), bll 99–109. kassel university press, Kassel, Germany, 2014.
  • "Know thyself" -- Computational Self-Reflection in Intelligent Technical Systems. Tomforde, S.; Hähner, J.; von Mammen, S.; Gruhl, C.; Sick, B.; Geihs, K. In Workshop on Self-Improving System Integration (SISSY), SASO. IEEE, Braunschweig, Germany, 2014.