Publications

Kristian G. Barman, Sascha Caron, Emily Sullivan, Henk W. de Regt, Roberto Ruiz de Austri, Mieke Boon, Michael Färber, Stefan Fröse, Tobias Golling, Luis G. Lopez, Faegheh Hasibi, Lukas Heinrich, Andreas Ipp, Rukshak Kapoor, Gregor Kasieczka, Daniel Kostić, Michael Krämer, Jesus Marco, Sydney Otten, Pawel Pawlowski, Pietro Vischia, Erik Weber, and Christoph Weniger. Large physics models: towards a collaborative approach with large language models and foundation models. The European Physical Journal C, (85)9:1066, Sep 25, 2025. [PUMA: LLMs foundation_models large models physics yaff] URL

Ferney Beltran-Velandia, Nico Scherf, and Martin Bogdan. A Pipeline based on Differential Evolution for Tuning Parameters of Synaptic Dynamics Models. ESANN 2025 proceesdings, 717–722, Ciaco - i6doc.com, 2025. [PUMA: dynamics models synaptic xack yaff] URL

Jens Christian Refsgaard, Juliane Mai, Markus Hrachowitz, Sharad K Jain, and Simon Stisen. Towards more credible models in catchment hydrology to enhance hydrological process understanding: Preface. Authorea, Inc., September 2023. [PUMA: catchment credible hydrological hydrology models process yaff]

Oliver Kirsten, Martin Bogdan, and Sophie Adama. Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: Complexity Computational Consciousness Information Locked-In Measures Modeling Neuroscience Prediction Predictive Processing Signal Syndrome Theory Training algorithms and data learning modeling models processing zno machine]

Emmanuel Donnadieu, Maik Luu, Miriam Alb, Brigitte Anliker, Silvia Arcangeli, Chiara Bonini, Biagio De Angelis, Rashmi Choudhary, David Espie, Anne Galy, Cam Holland, Zoltán Ivics, Chahrazade Kantari-Mimoun, Marie Jose Kersten, Ulrike Köhl, Chantal Kuhn, Bruno Laugel, Franco Locatelli, Ibtissam Marchiq, Janet Markman, Marta Angiola Moresco, Emma Morris, Helene Negre, Concetta Quintarelli, Michael Rade, Kristin Reiche, Matthias Renner, Eliana Ruggiero, Carmen Sanges, Hans Stauss, Maria Themeli, Jan Van den Brulle, Michael Hudecek, and Monica Casucci. Time to evolve: predicting engineered T cell-associated toxicity with next-generation models. Journal for ImmunoTherapy of Cancer, (10)5:e003486, BMJ, May 2022. [PUMA: T_cell-associated engineered models next-generation predicting toxicity zno] URL

Alexandra Sasha Luccioni, Christopher Akiki, Margaret Mitchell, and Yacine Jernite. Stable bias: evaluating societal representations in diffusion models. Proceedings of the 37th International Conference on Neural Information Processing Systems, Curran Associates Inc., Red Hook, NY, USA, 2024. [PUMA: Stable bias diffusion evaluating imported models representations societal yaff]

Jens Lehmann, Sébastien Ferré, and Sahar Vahdati. Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering. In Kobi Gal, Ann Nowé, Grzegorz J. Nalepa, Roy Fairstein, and Roxana Radulescu (Eds.), ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), (372):1348--1356, IOS Press, 2023. [PUMA: Answering Controlled Graph Knowledge Language Models Natural Parsers Question Semantic xack] URL

Claudio Hartmann, Martin Hahmann, Wolfgang Lehner, and Frank Rosenthal. Exploiting big data in time series forecasting: A cross-sectional approach. 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 1--10, 2015. [PUMA: Big Data Forecasting History Mathematical Predictive Time analysis data model models series zno]