J. Leineweber, Tagungsbericht: 10/20 Jahre UNESCO-Konvention zum Erhalt des Immateriellen Kulturerbes – Auftaktveranstaltung zum Doppeljubiläum. H-Soz-Kult, 2023.
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T. Janzen, S. Gabel, M. Gampert, F. Matz, and J. Reckermann, “Das DigitELE Tutorial: Eine digitale Lernumgebung in der Englischdidaktik,” in Digitalisierung in der Hochschullehre – Perspektiven und Gestaltungsoptionen, L. Mrohs, M. Hess, K. Lindner, J. Schlüter, and S. Overhage, Eds. Bamberg: University of Bamberg Press, 2023, pp. 151–154.
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M. Meyer, T. Kenter, and C. Plessl, “Multi-FPGA Designs and Scaling of HPC Challenge Benchmarks via MPI and Circuit-Switched Inter-FPGA Networks,”10.1145/3576200__ACM Transactions on Reconfigurable Technology and Systems, 2023, doi:10.1145/3576200 .
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J.-O. Opdenhövel, C. Plessl, and T. Kenter, “Mutation Tree Reconstruction of Tumor Cells on FPGAs Using a Bit-Level Matrix Representation,”10.1145/3597031.3597050__2023, doi:10.1145/3597031.3597050 .
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C. Demir and A.-C. Ngonga Ngomo, “Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras,” ECML-PKDD, 2023.
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C. Demir and A.-C. Ngonga Ngomo, “Neuro-Symbolic Class Expression Learning,” International Joint Conference on Artificial Intelligence, 2023.
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R. Schade, T. Kenter, H. Elgabarty, M. Lass, T. Kühne, and C. Plessl, “Breaking the exascale barrier for the electronic structure problem in ab-initio molecular dynamics,”10.1177/10943420231177631__The International Journal of High Performance Computing Applications, Art. no. 109434202311776, 2023, doi:10.1177/10943420231177631 .
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A. Tornede, Advanced Algorithm Selection with Machine Learning: Handling Large Algorithm Sets, Learning From Censored Data, and Simplyfing Meta Level Decisions. 2023.
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C. Offen and S. Ober-Blöbaum, “Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves,”10.1007/978-3-031-38271-0_57__in Geometric Science of Information, Saint-Malo, Palais du Grand Large, France, 2023, vol. 14071, pp. 569–579, doi:10.1007/978-3-031-38271-0_57 .
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S. Ober-Blöbaum and C. Offen, “Variational Learning of Euler–Lagrange Dynamics from Data,”10.1016/j.cam.2022.114780__Journal of Computational and Applied Mathematics, vol. 421, p. 114780, 2023, doi:10.1016/j.cam.2022.114780 .
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R. McLachlan and C. Offen, “Backward error analysis for conjugate symplectic methods,”10.3934/jgm.2023005__Journal of Geometric Mechanics, vol. 15, no. 1, pp. 98–115, 2023, doi:10.3934/jgm.2023005 .
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E. Dierkes, C. Offen, S. Ober-Blöbaum, and K. Flaßkamp, “Hamiltonian Neural Networks with Automatic Symmetry Detection,”10.1063/5.0142969__Chaos, vol. 33, no. 6, Art. no. 063115, 2023, doi:10.1063/5.0142969 .
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A. Sprenger, Testinstrumente und Testdatenanalyse zur Verarbeitung von Unsicherheiten in Logikblöcken hochintegrierter Schaltungen. Paderborn: Universität Paderborn, 2023.
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A. Baci and S. Heindorf, “Accelerating Concept Learning via Sampling,” 2023.
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S. Peitz, H. Harder, F. Nüske, F. Philipp, M. Schaller, and K. Worthmann, “Partial observations, coarse graining and equivariance in Koopman  operator theory for large-scale dynamical systems,” arXiv:2307.15325. 2023.
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arXiv: 2307.15325

Y. Karakaya, H. Somnitz, A. Hermsen, M. Gonchikzhapov, and T. Kasper, “Revisiting the initial reaction rates for TMS combustion and a new evidence for metastable silica nanoparticles in the gas-phase synthesis,”10.1016/j.jaecs.2023.100152__Applications in Energy and Combustion Science, vol. 14, Art. no. 100152, 2023, doi:10.1016/j.jaecs.2023.100152 .
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F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,”10.1007/s00332-022-09862-1__Journal of Nonlinear Science, vol. 33, Art. no. 14, 2023, doi:10.1007/s00332-022-09862-1 .
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S. S. Hotegni, S. Peitz, and M. B. Berkemeier, “Multi-Objective Optimization for Sparse Deep Neural Network Training,” arXiv:2308.12243. 2023.
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arXiv: 2308.12243

M. Gonchikzhapov and T. Kasper, “Thermal and chemical structure of ethanol and 2-ethylhexanoic acid/ethanol SpraySyn flames,”10.1016/j.jaecs.2023.100174__Applications in Energy and Combustion Science, vol. 15, Art. no. 100174, 2023, doi:10.1016/j.jaecs.2023.100174 .
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O. Wallscheid et al., “ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids,”10.21105/joss.05616__Journal of Open Source Software, vol. 8, no. 89, Art. no. 5616, 2023, doi:10.21105/joss.05616 .
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