L. Blübaum and S. Heindorf, “Causal Question Answering with Reinforcement Learning,” presented at the The Web Conference, Singapore.

N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis,”https://doi.org/10.1007/978-3-031-33455-9_13__in The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi:https://doi.org/10.1007/978-3-031-33455-9_13 .

L. N. Sieger, S. Heindorf, L. Blübaum, and A.-C. Ngonga Ngomo, “Counterfactual Explanations for Concepts in ELH,” arXiv:2301.05109. 2023.

A. Baci and S. Heindorf, “Accelerating Concept Learning via Sampling,” 2023.

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

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

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

S. Heindorf et al., “EvoLearner: Learning Description Logics with Evolutionary Algorithms,” in WWW, 2022, pp. 818–828.

L. N. Sieger et al., “User Involvement in Training Smart Home Agents,”10.1145/3527188.3561914__presented at the HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand, 2022, doi:10.1145/3527188.3561914 .

H. M. A. Zahera et al., “Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings,” in The Semantic Web: ESWC 2022 Satellite Events, Cham: Springer International Publishing, 2022.

A. Bondarenko et al., “CausalQA: A Benchmark for Causal Question Answering,” in Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 3296–3308.

S. Pestryakova et al., “CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications,” Scientific Data, 2022.

S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, and G. Tschirner-Vinke, “AI-Based Assistance System for Manufacturing.”10.1109/ETFA52439.2022.9921520__2022, doi:10.1109/ETFA52439.2022.9921520 .

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

H. M. A. Zahera, S. Heindorf, and A.-C. Ngonga Ngomo, “ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs,”10.1145/3460210.3493563__2021, doi:10.1145/3460210.3493563 .

R. Feldhans et al., “Drift Detection in Text Data with Document Embeddings,” in Intelligent Data Engineering and Automated Learning – IDEAL 2021, Cham: Springer International Publishing, 2021.

C. Demir, D. Moussallem, S. Heindorf, and A.-C. Ngonga Ngomo, “Convolutional Hypercomplex Embeddings for Link Prediction,” 2021.

T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts,”10.1109/wacv48630.2021.00204__2021, doi:10.1109/wacv48630.2021.00204 .

S. Heindorf, “Automatically generating instructions from tutorials for search and user navigation.” 2021.

S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, and M. Potthast, “CauseNet: Towards a Causality Graph Extracted from the Web,”10.1145/3340531.3412763__in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030, doi:10.1145/3340531.3412763 .