Informed Active Learning with Decision Trees to Balance Exploration and Exploitation
M. Schöne, B. Jaster, J. Bültemeier, M. Kohlhase, in: Institute for Data Science Solutions (Ed.), Kongress KI@HS Zukunft Im Fokus – Posterbeiträge, Hochschule Bielefeld, Bielefeld, 2025, pp. 26–27.

AI Workflow for Scarce Data: A Modular Approach to Optimise Processes
J. Bültemeier, C.-A. Holst, V. Lohweg, M. Schöne, B. Jaster, M. Kohlhase, in: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2025, pp. 1–4.

Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit
M. Schöne, B. Jaster, J. Bültemeier, J. Kösters, C.-A. Holst, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), IEEE, 2025, pp. 1–9.

Trust Issues in Active Learning and Their Impact on Real-World Applications
B. Jaster, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), IEEE, 2025, pp. 1–5.

Trust Issues in Active Learning and Their Impact on Real-World Applications
B. Jaster, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), IEEE, 2025, pp. 1–5.

Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit
M. Schöne, B. Jaster, J. Bültemeier, J. Kösters, C.-A. Holst, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), IEEE, 2025, pp. 1–9.

Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme 
V. Katter, B. Jaster, M. Schöne, Schriftenreihe des Institute for Data Science Solutions 2 (2024).

Active Learning for Regression Problems with Ensemble Methods
B. Jaster, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 33. Workshop Computational Intelligence, Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29.