| 2025 | FedCSIS | Do LLMs dream of antique hermeneutics? Critical remarks on automated text interpretation. | Jens Drpinghaus, Michael Tiemann |
| 2025 | FedCSIS | Modeling and optimizing flow networks with several constrains using sequential dynamical systems. | Jens Drpinghaus, Michael Tiemann, Robert Helmrich |
| 2025 | GI | Occupations and Education in X Data: How representative is the data? | Michael Tiemann, Jens Drpinghaus |
| 2025 | GI | Automated classification of German job titles according to KldB: Challenges and novel methods. | Ralf Dorau, Kristine Hein, Jens Drpinghaus, Michael Tiemann |
| 2025 | GI | An empirical analysis of incentive structures in German online job advertisements using a topic modeling approach. | Michelle Katharina Gassner, Michael Tiemann, Jens Drpinghaus |
| 2025 | GI | Talking about tasks or just sharing job offers? A case study on job-related tweets. | Kristine Hein, Michael Tiemann, Jens Drpinghaus |
| 2025 | GI | The perception of German occupations on YouTube: Gender and Skill biases in Video Recommendations. | Katerina Kostadinovska, Kristine Hein, Michael Tiemann |
| 2024 | GI | An analysis of Computer Science in OJAs with a dual-lingual ontology approach. | Michael Tiemann, Jens Drpinghaus, Venkatesh Hariharapura Shivashankar |
| 2024 | GI | Comparing a legacy tools taxonomy with digital tools from Computer Science Ontology. | Michael Tiemann, Jens Drpinghaus, Venkatesh Hariharapura Shivashankar, Ralf Dorau |
| 2023 | AAAI | Combining Slow and Fast: Complementary Filtering for Dynamics Learning. | Katharina Ensinger, Sebastian Ziesche, Barbara Rakitsch, Michael Tiemann, Sebastian Trimpe |
| 2023 | GI | What social media can tell us about essential occupations. | Michael Tiemann, Stefan Udelhofen, Lisa Fournier |
| 2023 | UAI | Baysian numerical integration with neural networks. | Katharina Ott, Michael Tiemann, Philipp Hennig, Franois-Xavier Briol |
| 2021 | ICLR | ResNet After All: Neural ODEs and Their Numerical Solution. | Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann |
| 2020 | ICML | Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems. | Hans Kersting, Nicholas Krmer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig |
| 2013 | ICSE | Water science software institute: an open source engagement process. | Stan Ahalt, Barbara S. Minsker, Michael Tiemann, Larry Band, Margaret Palmer, Ray Idaszak, Chris Lenhardt, Mary C. Whitton |