Harder, H., &; Peitz, S. (n.d.). Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines.
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Janicki, N., &; Tenberge, C. (n.d.). Technology education in elementary school using the example of arning robots” – development and evaluation of an in-service teacher training concept. Australasian Journal of Technology Education.
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Hoffmann, M., &; Biehler, R. (2023). Student Teachers ’ Knowledge of Congruence before a University Course on Geometry. In M. Trigueros, B. Barquero, R. Hochmuth, &; J. Peters (Eds.), Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022). University of Hannover and INDRUM.
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Kucklick, J.-P. (2023). HIEF: a holistic interpretability and explainability framework. Journal of Decision Systems, 1–41.https://doi.org/10.1080/12460125.2023.2207268 
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KOUAGOU, N. J., Heindorf, S., Demir, C., &; Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis. In C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, &; S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) (Vol. 13870, pp. 209–226). Springer International Publishing.https://doi.org/10.1007/978-3-031-33455-9_13 
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Ober-Blöbaum, S., &; Offen, C. (2023). Variational Learning of Euler–Lagrange Dynamics from Data. Journal of Computational and Applied Mathematics, 421, 114780.https://doi.org/10.1016/j.cam.2022.114780 
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Halimeh, H., Caron, M., &; Müller, O. (2023). Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features. Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences.
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Qudus, U., Röder, M., Kirrane, S., &; Ngomo, A.-C. N. (2023). TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs. In T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, &; J. Li (Eds.), The Semantic Web – ISWC 2023 (Vol. 14265, pp. 465–483). Springer, Cham.https://doi.org/10.1007/978-3-031-47240-4_25 
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Gräßler, I., &; Hieb, M. (2023). Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. Lectures, 253–524.https://doi.org/10.5162/smsi2023/d7.4 
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Schuldt, A., Palm, M., Neumann, P., Böhm-Kasper, O., Demmer, C., &; Lütje-Klose, B. (2023). eJede*r von uns sieht die Situation eben unterschiedlich 3 das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“. Zeitschrift Für Konzepte Und Arbeitsmaterialien Für Lehrer*innenbildung Und Unterricht, 5(4).https://doi.org/10.11576/DIMAWE-6699 
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Schneider, S. B., Werner, S., Khalili, R., Hecker, A., &; Karl, H. (2022). mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks. IEEE/IFIP Network Operations and Management Symposium (NOMS). IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest.
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Harteis, C., Gijbels, D., &; Kyndt, E. (Eds.). (2022). Research Approaches on Workplace Learning. Springer International Publishing.https://doi.org/10.1007/978-3-030-89582-2 
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Goller, M., &; Paloniemi, S. (2022). Agency: Taking Stock of Workplace Learning Research. In Research Approaches on Workplace Learning. Springer International Publishing.https://doi.org/10.1007/978-3-030-89582-2_1 
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Maalouly, J., Hemker, D., Hedayat, C., Rückert, C., Kaufmann, I., Olbrich, M., Lange, S., &; Mathis, H. (2022). AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development. 2022 Kleinheubach Conference. 2022 Kleinheubach Conference, Miltenberg, Germany.
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Sander, T., Lange, S., Hilleringmann, U., Geneiß, V., Hedayat, C., &; Kuhn, H. (2022). Detection of Defects on Irregularly Structured Surfaces using Supervised and Semi-Supervised Learning Methods. 2022 Smart Systems Integration (SSI). 2022 Smart Systems Integration (SSI), Grenoble, France.https://doi.org/10.1109/ssi56489.2022.9901433 
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Janicki, N. (2022). Entwicklung und Evaluation eines Fortbildungskonzepts im Kontext der technischen Bildung an Grundschulen am Beispiel von Lernrobotern. In M. Binder, C. Wiesmüller, &; T. Finkbeiner (Eds.), Technik: Verstehen wir, was wir nutzen!? - Tagungsband zur 23. Jahrestagung der Deutschen Gesellschaft für Technische Bildung in Mannheim vom 24.-25. September 2021.  (pp. 266–286).
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Sieger, L. N., Hermann, J., Schomäcker, A., Heindorf, S., Meske, C., Hey, C.-C., &; Dofangün, A. (2022). User Involvement in Training Smart Home Agents. International Conference on Human-Agent Interaction. HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand.https://doi.org/10.1145/3527188.3561914 
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Schön, O., Götte, R.-S., &; Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12), 19–24.https://doi.org/10.1016/j.ifacol.2022.07.282 
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Auer, T. F. (2022). Die Wirksamkeit von Lernzielen für Studienleistungen – eine experimentelle Studie. die hochschullehre, 8(1), 662–675.https://doi.org/10.3278/HSL2248W 
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Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., &; Trautmann, H. (2022). Process-Oriented Stream Classification Pipeline: A Literature Review. Applied Sciences, 12(18), 9094.https://doi.org/10.3390/app12189094 
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