Cloud Classification and Solar Irradiance Forecasting Using All-Sky Images
G. Behrens, Y. Ribouh, N. El Atmioui, in: 2025.

Prognose von Pegelständen mit Methoden des Maschinellen Lernens und frei verfügbaren Daten
G. Behrens, D. Marten, L. Koch, M. Gaj, in: F. Fuchs-Kittkowski, A. Abecker, F. Hosenfeld, A. Reineke, M. Möller, Springer (Eds.), Umweltinformationssysteme - Digitalisierung für eine nachhaltige Planetare Zukunft/ Tagungsband des 31. Workshops “Umweltinformationssysteme (UIS 2024)” der Fachgruppe “Umweltinformationssysteme” der Gesellschaft für Informatik (GI), Springer Fachmedien Wiesbaden; Springer Vieweg , Berlin, 2025.

Diagnosing Newton’s Solver Convergence Failures in the Initialization of Modelica Models
F. Casella, B. Bachmann, K. Abdelhak, P. Hannebohm, T. Van der Stelt, in: Proceedings of the 16th International Modelica&;FMI Conference, September 8 – 10, 2025, Lucerne University of Applied Sciences and Arts (HSLU), Linköping University Electronic Press, 2025.

Constant Time Causalization using Resizable Arrays
K. Abdelhak, B. Bachmann, in: Proceedings of the 16th International Modelica&;FMI Conference, September 8 – 10, 2025, Lucerne University of Applied Sciences and Arts (HSLU), Linköping University Electronic Press, 2025.

Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework
B. Bachmann, L. Bonaventura, F. Casella, S. Fernández-García, M. Gómez-Mármol, P. Hannebohm, Journal of Scientific Computing 105 (2025).

Enhancing Collocation-Based Dynamic Optimization through Adaptive Mesh Refinement
L. Langenkamp, B. Bachmann, in: D. Zimmer, U.C. Müller (Eds.), Proceedings of the 16th International Modelica&;FMI Conference, Linköping University Electronic Press, 2025, pp. 127–138.

Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming
L. Langenkamp, P. Hannebohm, B. Bachmann, in: D. Zimmer, U.C. Müller (Eds.), Proceedings of the 16th International Modelica&;FMI Conference, Linköping University Electronic Press, 2025, pp. 445–457.

Residual-Informed Learning of Solutions to Algebraic Loops
F. Brandt, A. Heuermann, P. Hannebohm, B. Bachmann, ArXiv:2510.09317 (2025).

Selective Evaluation of RHS during Multi-Rate Simulation
P. Hannebohm, B. Bachmann, in: D. Zimmer, U.C. Müller (Eds.), Proceedings of the 16th International Modelica&;FMI Conference, Linköping University Electronic Press, 2025, pp. 943–947.

Check or reject? Trust and motivation development in app-based warning systems
M. von der Linde, M. Göcke, G. Hirschfeld, M.T. Thielsch, Safety Science 185 (2025).

Fine-Tuning of Lightweight Large Language Models for Sentiment Classification on Heterogeneous Financial Textual Data
A.P. Amorin, A. Python, C. Weisser, Preprint (2025).

From Prediction to Proposal in Catalysis: Robust Evaluation, LRP Explanations, and Relevance-Guided Candidate Generation
P. Semnani, M. Bogojeski, F. Bley, Z. Zhang, Q. Wu, T. Kneib, J. Herrmann, C. Weisser, K.R. Müller, in: Openreview, 2025.

Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems
M. Niederhaus, N. Migenda, J. Weller, M. Kohlhase, W. Schenck, Big Data and Cognitive Computing 9 (2025).

Efficient Gait Analysis using Knowledge Distillation from Sparse Sensors
V. Katter, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut, Karlsruher Institut für Technologie (KIT) (Eds.), Proceedings – 35. Workshop Computational Intelligence: Berlin, 20.–21. November 2025, Karlsruher Institut für Technologie (KIT), Karlsruhe, 2025, pp. 89–96.

Incorporation of structural properties of the response surface into oblique model trees
M. Schöne, M. Kohlhase, O. Nelles, At - Automatisierungstechnik 73 (2025) 727–739.

Scheduling individualized products with reinforcement learning to reduce worker stress
L. Vogel, L. Vollenkemper, A. Müller, M. Kohlhase, in: S.-H. Sheu (Ed.), Preface: 2025 The 12th International Conference on Industrial Engineering and Applications (Europe), AIP Publishing, 2025.

Optical determination of the biomass particle size for Cellulosic Biofuel Production
P. Ulrich, C. Schwede, in: 2025 29th International Conference Information Visualisation (IV), IEEE, 2025, pp. 246–253.

Using Deep Learning to Improve Simulation-Based Decision Making by Process Lead Time Predictions
C. Schwede, A. Freiter, in: IEEE (Ed.), 2025 Winter Simulation Conference (WSC), IEEE, 2025, pp. 2989–3000.

Herausforderungen bei der Gestaltung hybrider Ausbildungs- und Einsatzszenarien für studentische Lehr- Lernbegleiter*innen: Praxisbeispiel Digital Learning Scouts an der Hochschule Bielefeld
H. Pruisken, N.A. Brockmann, A. Mersch, in: R. Küstermann, A. Schreiber, A. Mersch, Y. Fischer, M. Kunkel (Eds.), Digitalbaukasten für kompetenzorientiertes Selbststudium, 1st ed., Springer VS, Wiesbaden, 2025, pp. 109–142.

Probabilistic Topic Modelling With Transformer Representations
A. Reuter, A. Thielmann, C. Weisser, B. Säfken, T. Kneib, IEEE Transactions on Neural Networks and Learning Systems 36 (2025) 14551–14565.