Data Science und Ihre Anwendungen

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1. Yujing Ke; Kevin George; Kathan Pandya; David Blumenthal; Maximilian Sprang; Gerrit Großmann; Sebastian Vollmer; David Antony Selby

   BioDisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation

   In: Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. International Joint Conference on Artificial Intelligence (IJCAI-2026), 35th International Joint Conference on Artificial Intelligence, August 15-21, Bremen, Germany, IJCAI, 8/2026.

2. Harshita Katoch; David Antony Selby; Gerrit Großmann; Sebastian Vollmer

   Accounting for Bias Enables Sustainable LLM Evaluation

   In: Vitor Fortes Rey; René Schuster; Niklas Baumgarten; Sungho Suh; Tobias Christian Nauen (Hrsg.). International Joint Conference on Artificial Intelligence. IJCAI Workshop on Sustainability and Resource-Efficiency of Artificial Intelligence (SuRE-2026), 35th International Joint Conference on Artificial Intelligence, located at IJCAI-ECAI 2026, August 15-21, Bremen, Germany, CEUR-WS, ISBN 1613-0073, CEUR-WS, 8/2026.

3. Kanta Yamaoka; Sumantrak Mukherjee; Thomas Gärtner; David Antony Selby; Stefan Konigorski; Eyke Hüllermeier; Viktor Bengs; Sebastian Vollmer

   Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models

   In: ICML 2026 Workshop on Structured Data for Health. International Conference on Machine Learning (ICML-2026), Proceedings of the Workshop on Structured Data for Health, 7/2026.

4. Rashika Jakhmola; David Antony Selby; Mert Cihan; Dusan Prascevic; Elisabetta Petracci; Paola Ulivi; Enriqueta Felip; Rocío Caro Consuegra; Franco Stella; Piergiorgio Solli; Desideria Argnani; Milena Urbini; Johannes Urban Mayer; Sebastian Vollmer; Christian Martin; Jan Ewald; Maximilian Sprang

   MiracleNet: A biologically-interpretable machine learning model for resected non-small-cell lung cancer​

   In: Computational and Structural Biotechnology Journal, Vol. 0145, No. ja, Pages 1-26, American Association for the Advancement of Science, 6/2026.

5. Sara Farmahini Farahani

   Towards Personalized Cancer Immunotherapy: A Deep Learning Approach for Tumor-Specific T Cell Receptor Discovery

   Mastersthesis, University of Saarland, 2/2026.

6. Mohamed Karim Belaid; Maximilian Rabus; Eyke Hüllermeier

   Uncertainty Quantification in Pairwise Difference Learning for Classification

   In: Machine Learning, Vol. 115, No. 1, Pages 12-12, Springer, 2026.

7. Jan Tauberschmidt; Sophie Fellenz; Sebastian Vollmer; Andrew B. Duncan

   Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems

   In: The Fourteenth International Conference on Learning Representations. International Conference on Learning Representations (ICLR), located at ICLR-2026, April 23-27, Rio de Janeiro, Brazil, ICLR, 2026.

8. Siwei Ju; Jan Tauberschmidt; Oleg Arenz; Peter van Vliet; Jan Peters

   Behavior-Constrained Reinforcement Learning with Receding-Horizon Credit Assignment for High-Performance Control

   In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2604.03023, Pages 1-15, arXiv, 2026.

9. Peter Remmers; Aljoscha Burchardt; Birgit Beck

   23 Ethische Aspekte künstlicher Intelligenz

   In: Tanya Braun; Eyke Hüllermeier; Ute Schmid; Günther Görz. Handbuch der Künstlichen Intelligenz. Pages 749-768, ISBN 9783111386690, De Gruyter Oldenbourg, 2026.

10. Sumantrak Mukherjee; Mouad Elhamdi; George Mohler; David Antony Selby; Yao Xie; Sebastian Vollmer; Gerrit Großmann

    Neural Spatiotemporal Point Processes: Trends and Challenges

    In: Transactions on Machine Learning Research (TMLR), Vol. NA, Pages 1-27, JMLR, 11/2025.

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