Publications

In the EXPLAIN project, partners are engaged in research on AI systems and Machine Learning approaches. This section compiles all the publications produced throughout the project execution.

Industrial Artificial Intelligence and Applications

D. E. Baskan, D. Meyer, S. Mieck, L. Faubel, B. Klöpper, N. Strem, J. A. Wagner, and J. J. Koltermann, A Scenario-Based Model Comparison for Short-Term Day- Ahead Electricity Prices in Times of Economic and Political Tension. Algorithms, vol.16, no. 4, p.177 , March. 2023, doi: 10.3390/a16040177.

MLOps in Industry

L. Faubel, K. Schmid and H. Eichelberger, Is MLOps different in Industry 4.0? General and Specific Challenges , 3rd International Conference on Innovative Intelligent Industrial Production and Logistics (IN4PL) pp. 161-167. SciTePress., 2022, 10.5220/0011589600003329.

L. Faubel and K. Schmid, An Analysis of MLOps Practices, 1/2023, SSE 1/23/E, Software Systems Engineering, Institut für Informatik, Universität Hildesheim., 2023.

L.Faubel and K. Schmid, Review Protocol: A systematic literature review of MLOps, SSE 2/23/E, Stiftung Universität Hildesheim, August 2023

L.Faubel, T. Woudsma, L. Methnani, A. G. Ghezeljhemeidan, F. Buelow, K. Schmid,… M. Bång., (2023). Towards an MLOps Architecture for XAI in Industrial Applications. arXiv, 2309.12756.

L. Faubel, K.Schmid, & H. Eichelberger. MLOps Challenges in Industry 4.0. SN Comput. Sci., 4(6), 1–11. Doi: 10.1007/s42979-023-02282-2.

L. Faubel and Schmid, K. An MLOps Platform Comparison. (2024). Doi: 10.25528/197

L. Faubel and Schmid, K. MLOps: A Multiple Case Study in Industry 4.0. (2024) ArXiv, 2407.09107.

Human and Automation Interaction

A. Ramesh, M. Englund, A. Theodorou, R. Stolkin, and M. Chiou, Robot Health Indicator: A visual Cue to Improve Level of Autonomy Switching Systems. In: Variable Autonomy for human – robot Teaming (VAT) workshop, co – located with ACM/IEEE HRI 2023.

G. Manca, N. Bhattacharya, S. Maczey, D. Ziobro, E. Brorsson, and M. Bång, XAIProcessLens: A Counterfactual-Based Dashboard for Explainable AI in Process Industries,in Frontiers in Artificial Intelligence and Applications, vol. 368, HHAI 2023: Augmenting Human Intellect, pp. 401-403, doi: 10.3233/FAIA230110.

AI Governance

K. Baum, J. Bryson, F. Dignum, V. Dignum, M. Grobelnik, H. Hoos, M. Irgens, P. Lukowicz, C. Muller, F. Rossi, J. Shawe-Taylor, A. Theodorou and R. Vinuesa, From fear to action: AI governance and opportunities for all. 2023

Explainable AI in Industry

G. Manca, A. Fay, Explainable AI for Industrial flood classification using Counterfactuals, 2023.

G. Manca, F. C. Kunze, E. Brorsson and A. Fay, Dynamic Causal Analysis with Operator-Centric Visualization for Managing Industrial Alarm Floods, in: 2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference (ONCON)., 2023

Prior Work

Before setting up the EXPLAIN project, the project partners already worked towards the vision of AI systems that smartly interact with domain users. Here we collected the relevant prior work for the interested reader.