Discrepancy Modeling for Dynamical Systems
F.-M. Dockhorn, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 35. Workshop Computational Intelligence, Karlsruher Institut für Technologie (KIT), 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.

Sensorintegration in Orthesen zur Versorgung des Diabetischen Fußsyndroms: eine technische Betrachtung
V. Katter, C. Huperz, M. Kohlhase, Orthopädie Technik (2025) 68–73.

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.

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

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).

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.

An Application-oriented Review of Standard and Integral Sparse Identification of Nonlinear Dynamics
F.-M. Dockhorn, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024, KIT Scientific Publishing, 2024, pp. 53–76.

Dichte-skaliertes Optimierungskriterium für Sliced Latin Hypercube Designs
J. Bültemeier, M. Schöne, M. Kohlhase, C.-A. Holst, V. Lohweg, O. Nelles, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024, KIT Scientific Publishing, 2024, pp. 217–231.

Design decisions for integrating Prescriptive Analytics Use Cases into Smart Factories
J. Weller, N. Migenda, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, Procedia CIRP 128 (2024) 424–429.

Technical Readiness of Prescriptive Analytics Platforms: A Survey
M. Niederhaus, N. Migenda, J. Weller, W. Schenck, M. Kohlhase, in: IEEE (Ed.), 2024 35th Conference of Open Innovations Association (FRUCT), IEEE, 2024, pp. 509–519.

Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, R. Liu, A. Wegel, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, in: O. Niggemann, J. Beyerer, M. Krantz, C. Kühnert (Eds.), Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, Springer Nature Switzerland, Cham, 2024, pp. 89–100.

Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, Y. Naik, T. Heuwinkel, A. Kühn, M. Kohlhase, W. Schenck, R. Dumitrescu, Mathematics 12 (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.

Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops
L. Vollenkemper, F. Grumbach, M. Kohlhase, P. Reusch, Wt Werkstattstechnik Online 113 (2023) 158–163.

Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories
J. Weller, N. Migenda, A. Wegel, M. Kohlhase, W. Schenck, R. Dumitrescu, in: IEEE (Ed.), 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), IEEE, 2023, pp. 1–7.