@article{51158,
abstract = {{Extended Dynamic Mode Decomposition (EDMD) is a popular data-driven method to
approximate the Koopman operator for deterministic and stochastic (control)
systems. This operator is linear and encompasses full information on the
(expected stochastic) dynamics. In this paper, we analyze a kernel-based EDMD
algorithm, known as kEDMD, where the dictionary consists of the canonical
kernel features at the data points. The latter are acquired by i.i.d. samples
from a user-defined and application-driven distribution on a compact set. We
prove bounds on the prediction error of the kEDMD estimator when sampling from
this (not necessarily ergodic) distribution. The error analysis is further
extended to control-affine systems, where the considered invariance of the
Reproducing Kernel Hilbert Space is significantly less restrictive in
comparison to invariance assumptions on an a-priori chosen dictionary.}},
author = {{Philipp, Friedrich and Schaller, Manuel and Worthmann, Karl and Peitz, Sebastian and Nüske, Feliks}},
journal = {{ournal of Nonlinear Science}},
title = {{{Error analysis of kernel EDMD for prediction and control in the Koopman framework}}},
doi = {{10.1007/s00332-025-10182-3}},
volume = {{35}},
year = {{2025}},
}
@article{67319,
author = {{de Payrebrune, K. M. and Flaßkamp, K. and Ströhla, T. and Sattel, T. and Bestle, D. and Röder, B. and Eberhard, P. and Peitz, Sebastian and Stoffel, M. and Rutwik, G. and Aditya, B. and Wohlleben, M. and Sextro, W. and Raff, M. and Remy, C. D. and Yadav, M. and Stender, M. and van Delden, J. and Lüddecke, T. and Langer, S. C. and Schultz, J. and Blech, C.}},
journal = {{Technische Mechanik - European Journal of Engineering Mechanics}},
keywords = {{own, own-journal}},
number = {{1}},
pages = {{1–23}},
title = {{{The impact of AI on engineering design procedures for dynamical systems}}},
doi = {{10.24352/UB.OVGU-2025-037}},
volume = {{45}},
year = {{2025}},
}
@article{67317,
author = {{Berkemeier, Manuel and Peitz, Sebastian}},
journal = {{Open Journal of Mathematical Optimization}},
keywords = {{own, own-journal}},
pages = {{1–36}},
publisher = {{Université de Montpellier}},
title = {{{Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients}}},
doi = {{10.5802/ojmo.47}},
volume = {{6}},
year = {{2025}},
}
@article{67314,
author = {{Harder, Hans and Peitz, Sebastian and Nüske, Feliks and Philipp, Friedrich and Schaller, Manuel and Worthmann, Karl}},
journal = {{Physica D: Nonlinear Phenomena}},
keywords = {{own, own-journal}},
pages = {{134725}},
title = {{{Group Convolutional Extended Dynamic Mode Decomposition}}},
doi = {{10.1016/j.physd.2025.134725}},
volume = {{480}},
year = {{2025}},
}
@article{67316,
author = {{Peitz, Sebastian and Hotegni, Sedjro Salomon}},
journal = {{Machine Learning with Applications}},
keywords = {{own, own-journal}},
number = {{100700}},
title = {{{Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art}}},
doi = {{10.1016/j.mlwa.2025.100700}},
year = {{2025}},
}
@unpublished{67315,
author = {{Straat, Michiel and Markmann, Thorben and Peitz, Sebastian and Hammer, Barbara}},
booktitle = {{arXiv:2511.00272}},
keywords = {{own, own-preprint}},
title = {{{Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning}}},
year = {{2025}},
}
@unpublished{67318,
author = {{Fromme, Fynn and Allen-Blanchette, Christine and Harder, Hans and Peitz, Sebastian}},
booktitle = {{arXiv:2505.13569}},
keywords = {{own, own-preprint, erc}},
title = {{{Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders}}},
year = {{2025}},
}
@article{61016,
author = {{Baier, Dominik and Kieke, Laureen and Voth, Sven and Kloß, Marvin and Huck, Marten and Steinrück, Hans-Georg and Tiemann, Michael}},
issn = {{2379-3694}},
journal = {{ACS Sensors}},
number = {{8}},
pages = {{5664--5673}},
publisher = {{American Chemical Society (ACS)}},
title = {{{Selective H2 Gas Sensing Using ZIF-71/In-SnO2 Bilayer Sensors: A Size-Selective Molecular Sieving Approach}}},
doi = {{10.1021/acssensors.5c00770}},
volume = {{10}},
year = {{2025}},
}
@inproceedings{61202,
abstract = {{The number of datasets on the web of data increases continuously. However, the knowledge contained therein cannot be fully utilized without finding links between the entities contained in these datasets. Equivalent entities can not be identified solely by checking the equivalence of IRIs because of the different origins and naming schemes of different data providers. Yet, such equivalences can be discovered by computing the similarity of their attributes. In this paper we propose GLIDE, an approach that links entities from two different datasets by embedding a joint model of these datasets enriched by additional relations describing the similarity of literals. The joint model is embedded into a latent vector space while paying attention to juxtaposing similar literals. We evaluate our approach against state-of-the-art algorithms using real-world datasets commonly used in link discovery literature. The results show that GLIDE outperforms all baselines on 5 of 7 datasets with perfect or near-perfect accuracy. Our approach achieves its best performance on datasets that feature several literals with similarities. Our experiments indicate that researchers should not only pay attention to equal literals in knowledge graph embedding but should also be aware of the distance between similar literals.}},
author = {{Becker, Alexander and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed}},
booktitle = {{The Semantic Web – ISWC 2025}},
keywords = {{becker sherif enexa sailproject dice simba ngonga whale}},
title = {{{GLIDE: Knowledge Graph Linking using Distance-Aware Embeddings}}},
year = {{2025}},
}
@inproceedings{67338,
author = {{Becker, Alexander and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed}},
booktitle = {{OM 2025: The 20th International Workshop on Ontology Matching collocated with the 24th International Semantic Web Conference(ISWC 2025), November 2nd, 2025, Nara, Japan}},
keywords = {{becker dice enexa ngonga sailproject sherif whale}},
pages = {{166--171}},
publisher = {{CEUR-WS}},
title = {{{TIM Results for OAEI 2025}}},
volume = {{4144}},
year = {{2025}},
}
@inproceedings{67385,
author = {{Graner, Charlotte and Schettler, Sebastian and Hollmer, Katharina and Schöne, Sebastian and Kalich, Jan and Zimmermann, Martina}},
booktitle = {{43. Vortrags- und Diskussionstagung Werkstoffprüfung 2025 – Werkstoffe und Bauteile auf dem Prüfstand}},
isbn = {{978-3-88355-454-9}},
location = {{Dresden}},
pages = {{298--303 }},
title = {{{Mechanische Eigenschaften geclinchter Aluminiumverbindungen in Abhängigkeit vom Umformgrad}}},
year = {{2025}},
}
@inproceedings{67384,
author = {{Hollmer, Katharina and Reschke, Gregor and Brosius, Alexander and Zimmermann, Martina}},
booktitle = {{43. Vortrags- und Diskussionstagung Werkstoffprüfung 2025 – Werkstoffe und Bauteile auf dem Prüfstand}},
isbn = {{978-3-88355-454-9}},
location = {{Dresden}},
pages = {{220--226}},
title = {{{Analyse des Schädigungsverlaufs geclinchter Verbindungen während der Ermüdungsbeanspruchung}}},
year = {{2025}},
}
@misc{62985,
author = {{Cramer, Katja}},
publisher = {{LibreCat University}},
title = {{{Nutzen generativer künstlicher Intelligenz in der Physikunterrichtsplanung aus Sicht von Personen mit schulpraktischem Hintergrund.}}},
doi = {{10.13140/RG.2.2.32686.83523}},
year = {{2025}},
}
@inbook{45827,
author = {{Cao, Chuntian and Steinrück, Hans-Georg}},
booktitle = {{Reference Module in Chemistry, Molecular Sciences and Chemical Engineering}},
isbn = {{9780124095472}},
pages = {{391--416}},
publisher = {{Elsevier}},
title = {{{Molecular-scale synchrotron X-ray investigations of solid-liquid interfaces in lithium-ion batteries}}},
doi = {{10.1016/b978-0-323-85669-0.00105-7}},
year = {{2024}},
}
@misc{48363,
author = {{Foerster, Anne}},
booktitle = {{Women in Early Medieval England}},
editor = {{Butler, Emily and Dumitrescu, Irina}},
publisher = {{Springer Textbook}},
title = {{{The Swineherd’s Wife who Scolded the King}}},
year = {{2024}},
}
@misc{48362,
author = {{Foerster, Anne}},
booktitle = {{Women in Early Medieval England}},
editor = {{Butler, Emily and Dumitrescu, Irina}},
publisher = {{Springer Textbook}},
title = {{{Eadburh of Wessex}}},
year = {{2024}},
}
@misc{48364,
author = {{Foerster, Anne}},
booktitle = {{Women in Early Medieval England}},
editor = {{Butler, Emily and Dumitrescu, Irina}},
publisher = {{Springer Textbook}},
title = {{{Seaxburh}}},
year = {{2024}},
}
@inproceedings{48632,
abstract = {{Digital Servitization is one of the significant trends affecting the manufacturing industry. Companies try to tackle challenges regarding their differentiation and profitability using digital services. One specific type of digital services are smart services, which are digital services built on data from smart products. Introducing these kinds of offerings into the portfolio of manufacturing companies is not trivial. Moreover, they require conscious action to align all relevant capabilities to realize the respective business goals. However, what capabilities are generally relevant for smart services remains opaque. We conducted a systematic literature review to identify them and extended the results through an interview study. Our analysis results in 78 capabilities clustered among 12 principles and six dimensions. These results provide significant support for the smart service transformation of manufacturing companies and for structuring the research field of smart services.}},
author = {{Koldewey, Christian and Fichtler, Timm and Scholtysik, Michel and Biehler, Jan and Schreiner, Nick and Sommer, Franziska and Schacht, Maximilian and Kaufmann, Jonas and Rabe, Martin and Sedlmeier, Joachim and Dumitrescu, Roman}},
keywords = {{Digital Servitization, Transformation, Capabilities, Maturity, Smart Services}},
location = {{Hawaii}},
title = {{{Exploring Capabilities for the Smart Service Transformation in Manufacturing: Insights from Theory and Practice}}},
year = {{2024}},
}
@inproceedings{49354,
author = {{Afroze, Lameya and Merkelbach, Silke and von Enzberg, Sebastian and Dumitrescu, Roman}},
booktitle = {{ML4CPS 2023}},
location = {{Hamburg}},
title = {{{Domain Knowledge Injection Guidance for Predictive Maintenance}}},
year = {{2024}},
}
@inproceedings{49364,
author = {{Scholtysik, Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}},
title = {{{Business strategy taxonomy and solution patterns for the circular economy}}},
year = {{2024}},
}