Selected Publications

A collection of selected publications.

You can find a more on my Google Scholar profile.

An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning

Published in ECML PKDD, 2023

The role of the Rashomon effect in explainable machine learning

Recommended citation: Müller, S., Toborek, V., Beckh, K., Jakobs, M., Bauckhage, C., Welke, P. (2023). An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. In: Koutra, D., Plant, C., Gomez Rodriguez, M., Baralis, E., Bonchi, F. (eds) Machine Learning and Knowledge Discovery in Databases: Research Track. ECML PKDD 2023. Lecture Notes in Computer Science, vol 14171. Springer, Cham. https://arxiv.org/abs/2306.15786

Harnessing Prior Knowledge for Explainable Machine Learning: An Overview

Published in IEEE SaTML, 2023

How prior knowledge can be utilized for explainable machine learning

Recommended citation: K. Beckh, S. Müller, M. Jakobs, V. Toborek, H. Tan, R. Fischer, P. Welke, S. Houben, L. von Rueden. "Harnessing Prior Knowledge for Explainable Machine Learning: An Overview," 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), Raleigh, NC, USA, 2023, pp. 450-463 https://www.researchgate.net/publication/371243326_Harnessing_Prior_Knowledge_for_Explainable_Machine_Learning_An_Overview

Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems

Published in IEEE TKDE, 2021

Integration prior knowledge into the machine learning pipeline

Recommended citation: L. Von Rueden, S. Mayer, K. Beckh, B. Georgiev, S. Giesselbach, R. Heese, B. Kirsch, J. Pfrommer, A. Pick, R. Ramamurthy, M. Walczak, J. Garcke, C. Bauckhage, and J. Schuecker, “Informed Machine Learning – A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems,” IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 1, pp. 614-633 https://ieeexplore.ieee.org/abstract/document/9429985