Publications
Showing entries 1 - 20 out of 341
Roth A, Bause F, Kriege NM, Liebig T. Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph. In PMLR Proceedings of Machine Learning Research . Vol. 269. PMLR. 2025. p. 1-14. (Proceedings of Machine Learning Research (PMLR)).
Elting S, Ehmke JF, Gansterer M. Preference learning for efficient bundle selection in horizontal transport collaborations. European Journal of Operational Research. 2025 Aug 1;324(3):953-968. doi: 10.1016/j.ejor.2025.02.002
Wislocka A, Stücker J, Hahn O, Angulo RE. Excursion sets with a ‘perfect’ collapse model. Monthly Notices of the Royal Astronomical Society. 2025 Jul 7;541(2):880-898. doi: 10.1093/mnras/staf1029
Pühringer M, Thür N, Schnurer M, Lamp LM, Panzenboeck L, Hartler J et al. Automated mass spectrometry-based profiling of multi-glycosylated glycosyl inositol phospho ceramides (GIPC) reveals specific series GIPC rearrangements during barley grain development and heat stress response. Plant Journal. 2025 Jun;122(6):e70279. doi: 10.1111/tpj.70279
Zischg J, Bomze I. Novel shortcut strategies in copositivity detection: Decomposition for quicker positive certificates. Operations Research Perspectives. 2025 Jun;14:100324. Epub 2025 Jan. doi: 10.1016/j.orp.2024.100324
Bomze I, Rinaldi F, Zeffiro D. Projection free methods on product domains. Computational Optimization and Applications. 2025 Jun;91(2):511-540. doi: 10.1007/s10589-024-00585-5
Knoll C, Möller T, Gregory K, Koesten L. The Gulf of Interpretation: From Chart to Message and Back Again. 2025. Paper presented at CHI Conference on Human Factors in Computing Systems (CHI '25), Yokohama, Japan. doi: 10.1145/3706598.3713413
Kummer L, Gansterer W, Kriege NM. On the Relationship Between Robustness and Expressivity of Graph Neural Networks. In Proceedings of The 28th International Conference on Artificial Intelligence and Statistics. Vol. 258. PMLR. 2025. p. 1243-1251. (Proceedings of Machine Learning Research (PMLR)).
Teichmann L. The “Mapping German fiction in translation” dataset: Data collection, scope, and data quality. Journal of Cultural Analytics. 2025 Apr 22. doi: 10.22148/001c.128010
Kummer L, Moustafa S, Gansterer W, Kriege NM. Crossfire: An Elastic Defense Framework for Graph Neural Networks Under Bit Flip Attacks. In Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence. AAAI. 2025. p. 17990-17998. (Proceedings of the ... National Conference on Artificial Intelligence; No. 17, Vol. 39). doi: 10.1609/aaai.v39i17.33979
Cuchiero C, Primavera F, Guo SX. Functional Itô-formula and Taylor expansions for non-anticipative maps of càdlàg rough paths. 2025 Apr 8.
Johnsen LC, Meisel F, Ehmke JF. Stochastic stay times for interrelated trips in the rural dial-a-ride problem. Transportation Research Part E: Logistics and Transportation Review . 2025 Mar;195:103968. doi: 10.1016/j.tre.2025.103968
Maconi E, Alves J, Swiggum C, Ratzenböck S, Großschedl J, Köhler P et al. The Solar System's passage through the Radcliffe wave during the middle Miocene. Astronomy & Astrophysics. 2025 Feb 1.
Posch L, Alves J, Mirét-Roig N, Ratzenböck S, Großschedl J, Meingast S et al. The physical properties of Cluster Chains. Astronomy & Astrophysics. 2025 Jan 1;693:A175. doi: 10.1051/0004-6361/202451312
Mörth E, Sidak K, Maliga Z, Möller T, Gehlenborg N, Sorger P et al. Cell2Cell: Explorative Cell Interaction Analysis in Multi-Volumetric Tissue Data. IEEE Transactions on Visualization and Computer Graphics. 2025 Jan;31:569-579. doi: 10.1109/TVCG.2024.3456406
Schmude T, Koesten L, Möller T, Tschiatschek S. Information that matters: Exploring information needs of people affected by algorithmic decisions. International Journal of Human-Computer Studies. 2025 Jan;193:103380. Epub 2024 Sept 26. doi: 10.1016/j.ijhcs.2024.103380
Cuchiero C, Gazzani G, Möller JO, Papariello-Svaluto-Ferro S. Joint calibration to SPX and VIX options with signature-based models. Journal of Mathematical Finance. 2025 Jan;35(1):161-213. Epub 2024 Jul 31. doi: 10.1111/mafi.12442
Leiber C, Miklautz L, Plant C, Böhm C. An Introductory Survey to Autoencoder-based Deep Clustering - Sandboxes for Combining Clustering with Deep Learning. CoRR. 2025;abs/25.
Kriege NM, Seidel T, Humbeck L, Lessel U. Chemical Similarity and Substructure Searches. In Encyclopedia of Bioinformatics and Computational Biology (Second Edition). 2 ed. Vol. 3. Elsevier. 2025 doi: 10.1016/B978-0-323-95502-7.00048-8