Publications

Bowen Song, Chengjin Xu, Kossi Amouzouvi, Maocai Wang, Jens Lehmann, and Sahar Vahdati. Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs. Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part III, 601–616, Springer-Verlag, Berlin, Heidelberg, 2023. [PUMA: topic_knowledge] URL

Nishant Kumar, Sinisa Segvić, Abouzar Eslami, and Stefan Gumhold. Normalizing Flow Based Feature Synthesis for Outlier-Aware Object Detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5156-5165, June 2023. [PUMA: topic_visualcomputing]

Ni Li, Shorouq Zahra, Mariana Brito, Clare Flynn, Olof Görnerup, Koffi Worou, Murathan Kurfali, Chanjuan Meng, Wim Thiery, Jakob Zscheischler, Gabriele Messori, and Joakim Nivre. Using LLMs to Build a Database of Climate Extreme Impacts. Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024), 93–110, Association for Computational Linguistics, 2024. [PUMA: imported topic_earthenvironment] URL

Mohit Anand, Friedrich J. Bohn, Gustau Camps-Valls, Rico Fischer, Andreas Huth, Lily-belle Sweet, and Jakob Zscheischler. Identifying compound weather drivers of forest biomass loss with generative deep learning. Environmental Data Science, (3)Cambridge University Press (CUP), 2024. [PUMA: imported topic_earthenvironment] URL

Daniel Klotz, Martin Gauch, Frederik Kratzert, Grey Nearing, and Jakob Zscheischler. Technical Note: The divide and measure nonconformity – how metrics can mislead when we evaluate on different data partitions. Hydrology and Earth System Sciences, (28)15:3665–3673, Copernicus GmbH, August 2024. [PUMA: imported topic_earthenvironment] URL