Publikationen

Wissenschaftliche Publikationen des Instituts der letzten zwei Jahre

2023

  • Graph Pooling Provably Improves Expressivity. Lachi, Veronica; Moallemy-Oureh, Alice; Roth, Andreas; Welke, Pascal. In Workshop on New Frontiers in Graph Learning, NeurIPS. 2023.
  • DNN-Approximations of Control Laws for Nonlinear Systems with Polytopic Constraints. Markolf, L.; Stursberg, O. In Proc. of the 22nd IFAC World Congress, bll 1516–1521. 2023.
  • Leveraging Repeated Unlabelled Noisy Measurements to Augment Supervised Learning. Magnussen, Birk Martin; Stern, Claudius; Sick, Bernhard. In International Conference on Computational Intelligence and Intelligent Systems (CIIS). ACM, 2023.
  • The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset. Hetzel, Manuel; Reichert, Hannes; Reitberger, Günther; Doll, Konrad; Sick, Bernhard; Fuchs, Erich. In IEEE Intelligent Vehicles Symposium (IV), bll 1–7. IEEE, 2023.
  • Sensor Equivariance by LiDAR Projection Images. Reichert, Hannes; Hetzel, Manuel; Schreck, Steven; Doll, Konrad; Sick, Bernhard. In IEEE Intelligent Vehicles Symposium (IV), bll 1–6. IEEE, 2023.
  • Organic Computing -- Doctoral Dissertation Colloquium 2022. Tomforde, Sven; Krupitzer, Christian. In Vol. 24Intelligent Embedded Systems. kassel university press, 2023.
  • Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents. Lehna, Malte; Viebahn, Jan; Marot, Antoine; Tomforde, Sven; Scholz, Christoph. In Energy and AI, 14, bl 100276. Energy and AI, 2023.
  • A Unified Approach to Communication Delay and Communication Frequency in Distributed State Estimation of Linear Systems. Mast, J.; Liu, Z.; Wang, Z.; Stursberg, O. In IEEE Control Systems Letters, Volume 7, bll 2755–2760. 2023.
  • Model Predictive Control of PDEs for Temperature Control in 3D-Printing Processes. Schmidtke, V.; Rüger, M.; Stursberg, O. In Proc. of the 2023 European Control Conference, bll 496–501. 2023.
  • On the Design of Limit Cycles of Planar Switching Affine Systems. Hanke, N.; Stursberg, O. In Proc. of the 2023 European Control Conference, bll 2251–2256. 2023.
  • Sampling-based Uncertainty Estimation for an Instance Segmentation Network. Heidecker, Florian; El-Khateeb, Ahmad; Sick, Bernhard. In arXiv e-prints, bl arXiv:2305.14977. 2023.
  • Graph Neural Networks Designed for Different Graph Types: A Survey. Thomas, Josephine; Moallemy-Oureh, Alice; Beddar-Wiesing, Silvia; Holzhüter, Clara. In Transactions on Machine Learning Research. 2023.
  • Power flow forecasts at transmission grid nodes using Graph Neural Networks. Beinert, Dominik; Holzhüter, Clara; Thomas, Josephine; Vogt, Stephan. In Energy and AI, 14(1), bl 100262. Elsevier, 2023.
  • Tailored Output Layers of Neural Networks for Satisfaction of State Constraints in Nonlinear Control Systems. Markolf, L.; Stursberg, O. In Proceedings of the 2023 Annual American Control Conference (ACC), bll 1881–1888. 2023.
  • Towards Few-Shot Time Series Anomaly Detection with Temporal Attention and Dynamic Thresholding. Nivarthi, Chandana Priya; Sick, Bernhard. In International Conference on Machine Learning and Applications (ICMLA). IEEE, 2023.
  • Distributed Interval Estimation for Continuous-Time Linear Systems: A Two-Step Method. Wang, Z.; Zhang, J.; Liu, Z.; Han, W.; Shen, M. In Proc. of the 22nd IFAC World Congress, Volume 56(Issue 2), bll 8500–8505. 2023.
  • On Optimal Synchronization of Diffusively Coupled Heterogeneous Van Der Pol Oscillators. Trummel, T.; Liu, Z.; Stursberg, O. In IFAC-PapersOnLine, Volume 56(Issue 2), bll 9475–9480. 2023.
  • Distributed MPC of Uncertain Multi-Agent Systems Considering Formations and Obstacles. Flüs, P.; Stursberg, O. In Proc. of the 22nd IFAC World Congress, Volume 56(Issue 2), bll 10155–10161. 2023.
  • Reference Tracking for Constrained Uncertain Linear Systems by Stochastic MPC. Hahn, J.; Stursberg, O. In Proc. of the 22nd IFAC World Congress, 56(2), bll 10421–10427. 2023.
  • Reconstruction of incomplete X-ray diffraction pole figures of oligocrystalline materials using deep learning. Meier, David; Ragunathan, Rishan; Degener, Sebastian; Liehr, Alexander; Vollmer, Malte; Niendorf, Thomas; Sick, Bernhard. In Scientific Reports, 13(1), bl 5410. Springer Nature, 2023.
  • Utilizing Continuous Kernels for Processing Irregularly and Inconsistently Sampled Data With Position-Dependent Features. Magnussen, Birk Martin; Stern, Claudius; Sick, Bernhard. In International Conference on Autonomic and Autonomous Systems (ICAS), bll 49–53. ThinkMind, 2023.
  • Spatio-temporal LPV model of 2D workpiece temperature for Direct Laser Deposition. Pereira, Guilherme; Jelicic, Goran; Kroll, Andreas. In 22nd IFAC World Congress. IFAC, Yokohama, 2023.
  • An Airborne Measurement System to Detect, Locate and Quantify Methane Emissions. Kistner, Lars; Schmoll, Robert; Kroll, Andreas. In Sensor and Measurement Science International Conference (SMSI) 2023. AMA Verband für Sensorik und Messtechnik e.V., Nürnberg, 2023.
  • Integration of a High-Precision 3D Sensor into a 3D Thermography System. Mendez, Miguel; Schramm, Sebastian; Schmoll, Robert; Kroll, Andreas. In Sensor and Measurement Science International Conference (SMSI) 2023. AMA Verband für Sensorik und Messtechnik e.V., Nürnberg, 2023.
  • A Digital Twin for Part QualityPrediction and Control in Plastic Injection Molding. Rehmer, Alexander; Klute, Marco; Kroll, Andreas; Heim, Hans-Peter. In Modeling, Identification, and Control for Cyber-Physical Systems Towards Industry 4.0, 1st , P. Mercorelli, W. Zhang, H. Nemati, Y. Zhang (reds.). Elsevier, 2023.
  • Model-Based Optimization of Vaccination Strategies in Different Phases of Pandemic Virus Spread. Liu, Z.; Omayrat, M.; Stursberg, O. In Informatics in Control, Automation and Robotics. ICINCO 2021. Lecture Notes in Electrical Engineering, 1006, bll 185–208. 2023.
  • Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis. Botache, Diego; Dingel, Kristina; Huhnstock, Rico; Ehresmann, Arno; Sick, Bernhard. In arXiv e-prints, bl arXiv:2307.14294. 2023.
  • Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions. Nivarthi, Chandana Priya; Vogt, Stephan; Sick, Bernhard. In Machine Learning and Knowledge Extraction (MAKE), 5(3), bll 1214–1233. MDPI, 2023.
  • Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction. Huang, Zhixin; He, Yujiang; Sick, Bernhard. In Computational Science and Computational Intelligence (CSCI). IEEE, 2023.
  • Active Bird2Vec: Towards End-To-End Bird Sound Monitoring with Transformers. Rauch, Lukas; Schwinger, Raphael; Wirth, Moritz; Sick, Bernhard; Tomforde, Sven; Scholz, Christoph. In Workshop on Artificial Intelligence for Sustainability (AI4S), ECAI, bll 1–6. 2023.
  • Height Change Feature Based Free Space Detection. Schreck, Steven; Reichert, Hannes; Hetzel, Manuel; Doll, Konrad; Sick, Bernhard. In International Conference on Control, Mechatronics and Automation (ICCMA), bll 171–176. IEEE, 2023.
  • What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving. Breitenstein, Jasmin; Heidecker, Florian; Lyssenko, Maria; Bogdoll, Daniel; Bieshaar, Maarten; Zöllner, J. Marius; Sick, Bernhard; Fingscheidt, Tim. In Workshop on roBustness and Reliability of Autonomous Vehicles in the Open-world (BRAVO), ICCV, bll 3991–4000. 2023.
  • Time-aware Robustness of Temporal Graph Neural Networks for Link Prediction. Sälzer, Marco; Beddar-Wiesing, Silvia. In International Symposium on Temporal Representation and Reasoning (TIME), bll 19:1–19:3. 2023.
  • Targeted Adversarial Attacks on Wind Power Forecasts. Heinrich, René; Scholz, Christoph; Vogt, Stephan; Lehna, Malte. In Machine Learning, 113(2), bll 863–889. Springer, 2023.
  • Continuous Feature Networks: A Novel Method to Process Irregularly and Inconsistently Sampled Data With Position-Dependent Features. Magnussen, Birk Martin; Stern, Claudius; Sick, Bernhard. In International Journal On Advances in Intelligent Systems, 16(3&4), bll 43–50. ThinkMind, 2023.
  • Corner Cases in Machine Learning Processes. Heidecker, Florian; Bieshaar, Maarten; Sick, Bernhard. In AI Perspectives & Advances, 6(1), bll 1–17. 2023.
  • Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering. Aßenmacher, Matthias; Rauch, Lukas; Goschenhofer, Jann; Stephan, Andreas; Bischl, Bernd; Roth, Benjamin; Sick, Bernhard. In Workshop on Interactive Adapative Learning (IAL), ECML PKDD, bll 65–73. 2023.
  • It is the habit not the handle that affects tooth brushing. Results of a randomised counterbalanced cross over study. Deinzer, Renate; Eidenhardt, Zdenka; Sohrabi, Keywan; Stenger, Manuel; Kraft, Dominik; Sick, Bernhard; Götz-Hahn, Franz; Bottenbruch, Carlotta; Berneburg, Nils; Weik, Ulrike. In Research Square. 2023.
  • Model selection, adaptation, and combination for transfer learning in wind and photovoltaic power forecasts. Schreiber, Jens; Sick, Bernhard. In Energy and AI, 14, bl 100249. 2023.
  • Active Label Refinement for Semantic Segmentation of Satellite Images. Pham, Minh Tuan; Wijesingha, Jayan; Kottke, Daniel; Herde, Marek; Huseljic, Denis; Sick, Bernhard; Wachendorf, Michael; Esch, Thomas. In arXiv e-prints, bl arXiv:2309.06159. 2023.
  • ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. Rauch, Lukas; Aßenmacher, Matthias; Huseljic, Denis; Wirth, Moritz; Bischl, Bernd; Sick, Bernhard. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), bll 55–74. Springer, 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). 2023.
  • Self-Integration and Agent Compatibility. Gruhl, Christian; Sick, Bernhard. In Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), bll 71–73. IEEE, 2023.
  • An Examination of Organic Computing Strategies in Design Optimization. Decke, Jens. In Organic Computing -- Doctoral Dissertation Colloquium 2023, S. Tomforde, C. Krupitzer (reds.). kassel university press, 2023.
  • Resilience of Time-Varying Communication Graphs for Consensus of Changing Sets of Computing Agents. Schmidtke, V.; Liu, Z.; Stursberg, O. In 62nd IEEE Conference on Decision and Control, bll 3474–3479. 2023.
  • Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. Huang, Zhixin; He, Yujiang; Herde, Marek; Huseljic, Denis; Sick, Bernhard. In Workshop on Interactive Adapative Learning (IAL), ECML PKDD, bll 28–45. 2023.
  • Context Information for Corner Case Detection in Highly Automated Driving. Heidecker, Florian; Susetzky, Tobias; Fuchs, Erich; Sick, Bernhard. In IEEE International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2023.
  • On the Reliability of Automated Analysis of Fracture Surfaces Using a Novel Computer Vision-Based Tool. Engelhardt, Anna; Decke, Jens; Meier, David; Dulig, Franz; Ragunathan, Rishan; Wegener, Thomas; Sick, Bernhard; Niendorf, Thomas. In Advanced Engineering Materials, 25(21), bl 2300876. Wiley, 2023.
  • Role of Hyperparameters in Deep Active Learning. Huseljic, Denis; Herde, Marek; Hahn, Paul; Sick, Bernhard. In Workshop on Interactive Adaptive Learning (IAL), ECML PKDD, bll 19–24. 2023.
  • Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy. Sandrock, Christoph; Herde, Marek; Kottke, Daniel; Sick, Bernhard. In Discovery Science (DS), bll 265–276. Springer, 2023.
  • Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning. Herde, Marek; Huseljic, Denis; Sick, Bernhard; Bretschneider, Ulrich; Oeste-Reiß, Sarah. In Workshop on Interactive Adapative Learning (IAL), ECML PKDD, bll 14–18. 2023.
  • Multi-annotator Deep Learning: A Probabilistic Framework for Classification. Herde, Marek; Huseljic, Denis; Sick, Bernhard. In Transactions on Machine Learning Research. 2023.
  • Domain Imaging in Periodic Submicron Wide Nanostructures by Digital Drift Correction in Kerr Microscopy. Akhundzada, Sapida; Dingel, Kristina; Bischof, David; Janzen, Christian; Sick, Bernhard; Ehresmann, Arno. In Advanced Photonics Research, 4(10), bl 2300170. Wiley, 2023.
  • Context-aware recommendations for extended electric vehicle battery lifetime. Eider, Markus; Sick, Bernhard; Berl, Andreas. In Sustainable Computing: Informatics and Systems (SUSCOM), 37, bl 100845. Elsevier, 2023.

2022

  • Organic Computing -- Doctoral Dissertation Colloquium 2021. Tomforde, Sven; Krupitzer, Christian. In Vol. 20Intelligent Embedded Systems. kassel university press, 2022.
  • Actively Controlling and Redesigning Experiments using the Application Case of Free-Electron Laser Pulse Characterization. Dingel, Kristina. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 86–98. kassel university press, 2022.
  • Graph Neural Networks Designed for Different Graph Types: A Survey. Thomas, Josephine M.; Moallemy-Oureh, Alice; Beddar-Wiesing, Silvia; Holzhüter, Clara. In arXiv e-prints, bl arXiv:2204.03080. 2022.
  • Predicting flow stress behavior of an AA7075 alloy using machine learning methods. Decke, Jens; Engelhardt, Anna; Rauch, Lukas; Degener, Sebastian; Sajjadifar, Seyedvahid; Scharifi, Emad; Steinhoff, Kurt; Niendorf, Thomas; Sick, Bernhard. In Crystals, 9(12), bll 1–19. MDPI, 2022.
  • Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. Herde, Marek; Huang, Zhixin; Huseljic, Denis; Kottke, Daniel; Vogt, Stephan; Sick, Bernhard. In arXiv e-prints, bl arXiv:2210.06112. 2022.
  • FDGNN: Fully Dynamic Graph Neural Network. Moallemy-Oureh, Alice; Beddar-Wiesing, Silcia; Nather, Rüdiger; Thomas, Josephine M. In arXiv e-prints, bl arXiv:2206.03469. 2022.
  • A Review of Uncertainty Calibration in Pretrained Object Detectors. Huseljic, Denis; Herde, Marek; Muejde, Mehmet; Sick, Bernhard. In arXiv e-prints, bl arXiv:2210.02935. 2022.
  • A Holistic View on Probabilistic Trajectory Forecasting -- Case Study: Cyclist Intention Detection. Zernetsch, Stefan; Reichert, Hannes; Kress, Viktor; Doll, Konrad; Sick, Bernhard. In IEEE Intelligent Vehicles Symposium (IV), bll 265–272. IEEE, 2022.
  • Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning. He, Yujiang; Huang, Zhixin; Sick, Bernhard. In Workshop on Interactive Machine Learning Workshop (IMLW), AAAI, bll 1–6. 2022.
  • On Stability of Network Control Systems with Switching Transmission Probabilities. Hahn, Jannik; Stursberg, Olaf. In IFAC-PapersOnLine, 55(13), bll 276–281. 2022.
  • Distributed Solution of Mixed-Integer Programs by ADMM with Closed Duality Gap. Liu, Zonglin; Stursberg, Olaf. In 61st IEEE Conference on Decision and Control (CDC). 2022.
  • Efficient Fault Detection for Discrete-Time PWA Systems,. Liu, Xinyang; Liu, Zonglin; Wang, Zhenhua; Stursberg, Olaf. In IEEE Control Systems Letters, 6, bll 3361–3366. 2022.
  • Distributed Optimization for Mixed-Integer Consensus in Multi-Agent Networks. Liu, Zonglin; Stursberg, Olaf. In 2022 European Control Conference (ECC), bll 2196–2202. 2022.
  • Active Learning in Multivariate Time Series Anomaly Detection. Huang, Zhixin. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 113–124. kassel university press, 2022.
  • Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems. Nivarthi, Chandana Priya. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 47–59. kassel university press, 2022.
  • Optimizing a superconducting radio-frequency gun using deep reinforcement learning. Meier, David; Ramirez, Luis Vera; Völker, Jens; Viefhaus, Jens; Sick, Bernhard; Hartmann, Gregor. In Physical Review Accelerators and Beams, 25(10), bl 104604. American Physical Society, 2022.
  • Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power Forecasts. He, Yujiang. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 125–140. kassel university press, 2022.
  • Stream-Based Active Learning in Changing Environments under Verification Latency. Pham, Tuan. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 152–164. kassel university press, 2022.
  • Student Research Abstract: Using Local Activity Encoding for Dynamic Graph Pooling in Stuctural-Dynamic Graphs. Beddar-Wiesing, Silvia. In ACM/SIGAPP Symposium on Applied Computing (SAC), bll 604–609. ACM, 2022.
  • Student Research Abstract: Continuous-Time Generative Graph Neural Network for Attributed Dynamic Graphs. Moallemy-Oureh, Alice. In ACM/SIGAPP Symposium on Applied Computing (SAC), bll 600–603. ACM, 2022.
  • Using AoI Forecasts in Communicating and Robust Distributed Model-Predictive Control. Hahn, Jannik; Schoeffauer, Richard; Wunder, Gerhard; Stursberg, Olaf. In IEEE Transactions on Control of Network Systems, 9(2), bll 742–752. 2022.
  • Uncertain AoI in stochastic optimal control of constrained LTI systems. Hahn, Jannik; Stursberg, Olaf. In at - Automatisierungstechnik, 70(4), bll 343–354. 2022.
  • Zum strukturvorwissensbasierten Testsignalentwurf mittels Vorsteuerung für die Identifikation von Takagi-Sugeno-Modellen. Himmelsbach, Matthias; Kroll, Andreas. In at -- Automatisierungstechnik, 70(2), bll 119–133. 2022.
  • A Deep Recurrent Neural Network model for affine quasi-LPV System identification. Rehmer, Alexander; Kroll, Andreas. In Preprints of the 20th European Control Conference (ECC). London, UK, 2022.
  • Method and Experimental Investigation of Surface Heat Dissipation Measurement using 3D Thermography. Schmoll, Robert; Schramm, Sebastian; Breitenstein, Tom; Kroll, Andreas. In Journal of Sensors and Sensor Systems (JSSS) - Sensors and Measurement Science International (SMSI) 2021 Special Issue, November, bll 41–49. 2022.
  • Compensating the Size-of-Source Effect: Relationship between the MTF and a Data-Driven Convolution Filter Approach. Schramm, Sebastian; Ebert, Jannik; Schmoll, Robert; Kroll, Andreas. In 16th Quantitative InfraRed Thermography Conference (QIRT). Paris, Frankreich, 2022.
  • Calibration and validation of micromagnetic data for non-destructive analysis of near-surface properties after hard turning. Wegener, Thomas; Liehr, Alexander; Bolender, Artjom; Degener, Sebastian; Wittich, Felix; Kroll, Andreas; Niendorf, Thomas. In HTM Journal of Heat Treatment and Materials. 2022.
  • Control of Jump Markov Uncertain Linear Systems With General Probability Distributions. Flues, Patrick; Stursberg, Olaf. In Frontiers of Control Eng., Vol 3. 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.
  • Efficient SVDD sampling with approximation guarantees for the decision boundary. Englhardt, Adrian; Trittenbach, Holger; Kottke, Daniel; Sick, Bernhard; Böhm, Klemens. In Machine Learning, 111(4), bll 1349–1375. Springer, 2022.
  • A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning. Herde, Marek; Huseljic, Denis; Mitrovic, Jelena; Granitzer, Michael; Sick, Bernhard. In Workshop on Interactive Adaptive Learning (IAL), ECML PKDD, bll 1–6. 2022.
  • Self-Adaptive Charging Management in Electric Vehicle Infrastructures based on Reinforcement Learning. Hassouna, Mohamed. In Organic Computing -- Doctoral Dissertation Colloquium 2022, S. Tomforde, C. Krupitzer (reds.), bll 1–16. kassel university press, 2022.
  • An internal dynamics approach to predicting batch-end product quality in plastic injection molding using Recurrent Neural Networks. Rehmer, Alexander; Klute, Marco; Kroll, Andreas; Heim, Hans-Peter. In IFAC-PapersOnLine, Vol. 53, bll 1427–1432. Elsevier, Trieste, Italy, 2022.
  • Deep Adaptive Knowledge-Aware Learning for E-Mobility. Ali, Mohammad Wazed. In Organic Computing - Doctoral Dissertation Colloquium 2022, S. Tomforde, C. Krupitzer (reds.), bll 139–155. kassel university press, 2022.
  • Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users Trajectories. Kress, Viktor; Jeske, Fabian; Zernetsch, Stefan; Doll, Konrad; Sick, Bernhard. In IEEE Transactions on Intelligent Vehicles, 8(3), bll 2592–2603. IEEE, 2022.
  • Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs. Beddar-Wiesing, Silvia; D’Inverno, Giuseppe Alessio; Graziani, Caterina; Lachi, Veronica; Moallemy-Oureh, Alice; Scarselli, Franco; Thomas, Josephine. In arXiv e-prints, bl arXiv:2210.03990. 2022.
  • Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting. Nivarthi, Chandana Priya; Vogt, Stephan; Sick, Bernhard. In International Conference on Machine Learning and Applications (ICMLA), bll 1530–1536. IEEE, 2022.
  • A Stopping Criterion for Transductive Active Learning. Kottke, Daniel; Sandrock, Christoph; Krempl, Georg; Sick, Bernhard. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), bll 468–484. Springer, 2022.
  • Detecting Corner Case in the Context of Highly Automated Driving. Heidecker, Florian. In Organic Computing -- Doctoral Dissertation Colloquium 2021, S. Tomforde, C. Krupitzer (reds.), bll 60–73. kassel university press, 2022.
  • Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving. Rösch, Kevin; Heidecker, Florian; Truetsch, Julian; Kowol, Kamil; Schicktanz, Clemens; Bieshaar, Maarten; Sick, Bernhard; Stiller, Christoph. In IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (IEEE CIVTS), IEEE SSCI, bll 86–93. IEEE, 2022.
  • Approximation of the Feasible Parameter Set in Bounded-Error Parameter Estimation of Takagi-Sugeno Fuzzy Models for Large Problems by Using a Ray Shooting Method. Wittich, Felix; Kroll, Andras. In Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2022). Padua, Italy, 2022.
  • Method and Experimental Investigation of Surface Heat Dissipation Measurement using 3D Thermography. Schmoll, Robert; Schramm, Sebastian; Breitenstein, Tom; Kroll, Andreas. In Journal of Sensors and Sensor Systems (JSSS), 11, bll 41–49. 2022.
  • Predicting the compressive strength of concrete up to 28 days-ahead: Comparison of machine learning algorithms on benchmark datasets. Rezazadeh, Farzad; Kroll, Andreas. In 32. Workshop Computational Intelligence, bll 53–75. KIT Scientific Publishing, Berlin, 2022.
  • Investigation of processing windows in additive manufacturing of AlSi10Mg for faster production utilizing data-driven modelling. Engelhardt, A; Kahl, M; Richter, J; Krooß, P; Kroll, A; Niendorf, T. In Additive Manufacturing, 55. Elsevier, 2022.
  • The effect of the forget gate on bifurcation boundaries and dynamics in Recurrent Neural Networks and its implications for gradient-based optimization. Rehmer, Alexander; Kroll, Andras. In Preprints of the International Joint Conference on Neural Networks (IJCNN 2022), bll 1–8. Padua, Italy, 2022.
  • Eine Python-Toolbox zur datengetriebenen Modellierung des Spritzgieprozsses und Lösung von Optimalsteuerungsproblemen zur Steuerung der Bauteilqualität. Rehmer, Alexander; Kroll, Andreas. In 32. Workshop Computational Intelligence, bll 133–150. KIT Scientific Publishing, Berlin, 2022.
  • Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources. Rauch, Lukas; Huseljic, Denis; Sick, Bernhard. In Workshop on Interactive Adaptive Learning (IAL), ECML PKDD, bll 27–42. 2022.
  • On affine quasi-LPV System Identification with unknown state-scheduling using (deep) Recurrent Neural Networks. Rehmer, Alexander; Kroll, Andreas. In IFAC-PapersOnLine, bll 446–451. Sinaia, Romania, 2022.
  • Calibration and validation of micromagnetic data for non-destructive analysis of near-surface properties after hard turning. Wegener, Thomas; Liehr, Alexander; Bolender, Artjom; Degener, Sebastian; Wittich, Felix; Kroll, Andreas; Niendorf, Thomas. In HTM Journal of Heat Treatment and Materials, 77(2), bll 156–172. 2022.
  • LwTool: A data processing toolkit for building a real-time pressure mapping smart textile software system. Guo, Tao; Huang, Zhixin; Cheng, Jingyuan. In Pervasive and Mobile Computing, 80, bl 101540. Elsevier, 2022.
  • Multi-Task Autoencoders and Transfer Learning for Day-Ahead Wind and Photovoltaic Power Forecasts. Schreiber, Jens; Sick, Bernhard. In Energies, 15(21), bl 8062. MDPI, 2022.
  • On the Extension of the Weisfeiler-Lehman Hierarchy by WL Tests for Arbitrary Graphs. Beddar-Wiesing, Silvia; D’Inverno, Giuseppe Alessio; Graziani, Caterina; Lachi, Veronica; Moallemy-Oureh, Alice; Scarselli, Franco. In Workshp on Mining and Learning on Graphs (MLG), ECML PKDD, bll 1–13. 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.
  • 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.
  • Self-Aware Microsystems. Gruhl, Christian; Tomforde, Sven; Sick, Bernhard. In Workshop on Self-Improving System Integration (SISSY), ACSOS, bll 126–127. IEEE, 2022.
  • Three-dimensional close-to-substrate trajectories of magnetic microparticles in dynamically changing magnetic field landscapes. Huhnstock, Rico; Reginka, Meike; Sonntag, Claudius; Merkel, Maximilian; Dingel, Kristina; Sick, Bernhard; Vogel, Michael; Ehresmann, Arno. In Scientific Reports, 12(1), bll 1–10. Springer Nature, 2022.
  • Heterogeneous Multi-Source Deep Adaptive Knowledge-Aware Learning for E-Mobility. Ali, Mohammad Wazed. In IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), bll 57–60. IEEE, 2022.
  • Receding-Horizon Control of Constrained Switched Systems with Neural Networks as Parametric Function Approximators. Markolf, Lukas; Stursberg, Olaf. In SN Computer Science, 4(62). 2022.
  • Artificial intelligence for online characterization of ultrashort X‑ray free‑electron laser pulses. Dingel, Kristina; Otto, Thorsten; Marder, Lutz; Funke, Lars; Held, Arne; Savio, Sara; Hans, Andreas; Hartmann, Gregor; Meier, David; Viefhaus, Jens; Sick, Bernhard; Ehresmann, Arno; Ilchen, Markus; Helml, Wolfram. In Scientific Reports, 12(1), bll 1–14. Nature Publishing Group, 2022.
  • A Practical Evaluation of Active Learning Approaches for Object Detection. Schneegans, Jan; Bieshaar, Maarten; Sick, Bernhard. In Workshop on Interactive Adaptive Learning (IAL), ECML PKDD, bll 49–67. 2022.
  • 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.