Class Expression Learning with Multiple Representations
A.-C. Ngonga Ngomo, C. Demir, N.J. Kouagou, S. Heindorf, N. Karalis, A. Bigerl, in: Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 272–286.

LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals
C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD (2023).

Neural Class Expression Synthesis in ALCHIQ(D)
N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.

Explaining ELH Concept Descriptions through Counterfactual Reasoning
L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109 (2023).

Accelerating Concept Learning via Sampling
A. Baci, S. Heindorf, in: CIKM, 2023, pp. 3733–3737.

TaOnto: Unsupervised Semantification with Knowledge Graph Embeddings
H.M.A. Zahera, S. Heindorf, S. Balke, J. Haupt, M. Voigt, C. Walter, F. Witter, A.-C. Ngonga Ngomo, in: The Semantic Web: ESWC 2022 Satellite Events, Springer International Publishing, Cham, 2022.

CausalQA: A Benchmark for Causal Question Answering
A. Bondarenko, M. Wolska, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, B. Stein, P. Braslavski, M. Hagen, M. Potthast, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 3296–3308.

AI-Based Assistance System for Manufacturing
S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke, (2022).

Learning Concept Lengths Accelerates Concept Learning in ALC
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: The Semantic Web, Springer International Publishing, Cham, 2022.

EvoLearner: Learning Description Logics with Evolutionary Algorithms
S. Heindorf, L. Blübaum, N. Düsterhus, T. Werner, V.N. Golani, C. Demir, A.-C. Ngonga Ngomo, in: WWW, ACM, 2022, pp. 818–828.

CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications
S. Pestryakova, D. Vollmers, M. Sherif, S. Heindorf, M. Saleem, D. Moussallem, A.-C. Ngonga Ngomo, Scientific Data (2022).

User Involvement in Training Smart Home Agents
L.N. Sieger, J. Hermann, A. Schomäcker, S. Heindorf, C. Meske, C.-C. Hey, A. Dofangün, in: International Conference on Human-Agent Interaction, ACM, 2022.

Drift Detection in Text Data with Document Embeddings
R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, Cham, 2021.

Convolutional Hypercomplex Embeddings for Link Prediction
C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian Conference on Machine Learning, ACML 2021, 2021.

Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts
T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, 2021.

Automatically generating instructions from tutorials for search and user navigation
S. Heindorf, (2021).

ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs
H.M.A. Zahera, S. Heindorf, A.-C. Ngonga Ngomo, in: Proceedings of the 11th on Knowledge Capture Conference, ACM, 2021.

CauseNet: Towards a Causality Graph Extracted from the Web
S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, M. Potthast, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030.

Debiasing Vandalism Detection Models at Wikidata
S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: WWW, ACM, 2019, pp. 670–680.

Vandalism Detection in Crowdsourced Knowledge Bases
S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases, Universität Paderborn, 2019.