Low Query Budget Active Learning for Classification and Regression
B. Jaster, A. Tharwat, E.M. Sheikh, M. Kohlhase, W. Schenck, in: I. Koprinska, J. Mendes-Moreira, P. Branco (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases. International Workshops of ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Revised Selected Papers, Part IV, Springer Nature Switzerland, Cham, 2026, pp. 5–21.

Active learning evaluation metrics for classification and regression frameworks
A. Tharwat, B. Jaster, W. Schenck, M. Kohlhase, Engineering Applications of Artificial Intelligence 171 (2026).

H-NGPCA: Hierarchical clustering of data streams with adaptive number of clusters and adaptive dimensionality
N. Migenda, R. Möller, W. Schenck, PLOS One 21 (2026).

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).

Cognitive Edge Computing for Multi-Sensor Applications with Sparse Data and High Latency Requirements
J. Leuering, F. Jalil, Q.A. Ahmed, W. Schenck, T. Jungeblut, in: Institute for Data Science Solutions, Bielefeld, n.d.

NNXC: Neural Network Meets Approximate Computing
F. Jalil, J. Leuering, Q.A. Ahmed, W. Schenck, T. Jungeblut, in:  Institute for Data Science Solutions, Bielefeld, 2025.

AutoDSE: Towards HW/AI Co-design of Ultra-low Latency Hardware Accelerators for Industrial Applications
F. Jalil, J. Leuering, Q.A. Ahmed, W. Schenck, T. Jungeblut, in: Workshop on AI and Its Applications, Institute for Data Science Solutions, Bielefeld, 2025.

Softwaregestützte Analyse geriatrischer Entlassbriefe
T.C. Herzig, C. Marschner, C. Ostrau, S. Held, J. Rickermann, W. Schenck, A. Uphaus, R. Amelung, Zeitschrift für Gerontologie und Geriatrie (2025).

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).

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.

Adaptive local Principal Component Analysis improves the clustering of high-dimensional data
N. Migenda, R. Möller, W. Schenck, Pattern Recognition 146 (2024).

Transferability of Non-contrastive Self-supervised Learning to Chronic Wound Image Recognition
J.M. Akay, W. Schenck, in: M. Wand, K. Malinovská, J. Schmidhuber, I.V. Tetko (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2024. 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VIII, Springer Nature Switzerland, Cham, 2024, pp. 427–444.

Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget
A. Tharwat, W. Schenck, IEEE Transactions on Knowledge and Data Engineering 36 (2024) 4317–4330.

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.

Sustainable Life-Cycle of Intelligent Socio-Technical Systems
B. Hammer, Ö. Alaçam, C.S. Arlinghaus, M. Brinkmann, H. Dörksen, S. Hoeken, T. Jungeblut, J. Knaup, D. Leite, V. Lohweg, G.W. Maier, A.-C. Ngonga Ngomo, A. Othman, S. Peitz, M. Platzner, O. Pütz, C. Röcker, M. Röder, W. Schenck, A. Schneider, S. Schwandt, S. Spliethoff, M. Straat, B.G. Sürmeli, A.-L. Vollmer, S. Zarrieß, Sustainable Life-Cycle of Intelligent Socio-Technical Systems, Bielefeld University, 2024.

Image restoration in frequency space using complex-valued CNNs
Z.H. Shah, M. Müller, W. Hübner, H. Ortkrass, B. Hammer, T. Huser, W. Schenck, Frontiers in Artificial Intelligence 7 (2024).

Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data
Z.H. Shah, M. Müller, W. Hübner, T.-C. Wang, D. Telman, T. Huser, W. Schenck, GigaScience 13 (2024).

Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget
A. Tharwat, W. Schenck, IEEE Transactions on Knowledge and Data Engineering 36 (2024) 4317–4330.

Active Learning for Handling Missing Data
A. Tharwat, W. Schenck, IEEE Transactions on Neural Networks and Learning Systems 36 (2024) 3273–3287.

Exploratory Analysis of Machine Learning Methods for the Prognosis of Falls in Elderly Care Based on Accelerometer Data
L. Klein, C. Ostrau, M. Thies, W. Schenck, U. Rückert, in: D. Salvi, P. Van Gorp, S.A. Shah (Eds.), Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malmö, Sweden, November 27-29, 2023, Proceedings, Springer Nature Switzerland, Cham, 2024, pp. 423–437.