A. Tornede, Advanced Algorithm Selection with Machine Learning: Handling Large Algorithm Sets, Learning From Censored Data, and Simplyfing Meta Level Decisions. 2023.

I. Gräßler and D. Preuß, “Automatisierte Abhängigkeitsanalyse von Anforderungen zur Wirkkettenmodellierung,” in Stuttgarter Symposium für Produktentwicklung SSP 2023, Stuttgart, 2023.

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 .

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 .

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 .

H. M. A. Zahera, F. Vitiugin, M. Sherif, C. Castillo, and A.-C. Ngonga Ngomo, “Using Pre-trained Language Models for Abstractive DBpedia Summarization: A Comparative Study,” presented at the SEMANTiCS 2023, Leipzig, Germany, 2023.

C. Greiff et al., “Calibration of Large Coherent MIMO Radar Arrays: Channel Imbalances and 3D Antenna Positions,”10.23919/IRS57608.2023.10172475__presented at the 2023 24th International Radar Symposium (IRS), Berlin, Germany, 2023, doi:10.23919/IRS57608.2023.10172475 .

N. Vöing, M. Arnold, and S. Reisas, Lehrentwicklung durch Scholarship of Teaching and Learning – mit SoTL Hochschullehre beforschen, weiterentwickeln und teilen. e-teaching.org, 2023.

M. Arnold, N. Vöing, and S. Reisas, “Scholarship of Teaching and Learning (SoTL) als Motor für eine inter- und transdisziplinäre Hochschuldidaktik,” in Hochschulbildung: Lehre und Forschung, Bielefeld, Germany: transcript Verlag, 2023.

S. S. Hotegni, S. Peitz, and M. B. Berkemeier, “Multi-Objective Optimization for Sparse Deep Neural Network Training,” arXiv:2308.12243. 2023.

M. Dellnitz et al., “Efficient time stepping for numerical integration using reinforcement  learning,”10.1137/21M1412682__SIAM Journal on Scientific Computing, vol. 45, no. 2, pp. 9–5, 2023, doi:10.1137/21M1412682 .

M. Arnold, N. Vöing, and S. Reisas, “Scholarship of Teaching and Learning (SoTL) als Motor für eine inter- und transdisziplinäre Hochschuldidaktik,” in Hochschulbildung: Lehre und Forschung, Bielefeld, Germany: transcript Verlag, 2023.

M. Rossel and G. Meschut, “Modeling and Parameterization for a 3D Simulation of Clinching with an Extensible Die,” in Lecture Notes in Mechanical Engineering, Cham: Springer Nature Switzerland, 2023.

R. Reeschke, F. K. Haase, L. Dautzenberg, W. Krutsch, and C. Reinsberger, “Training matters: Heading incidence and characteristics in children’s and youth football (soccer) players,”10.1111/sms.14408__Scandinavian Journal of Medicine &; Science in Sports, vol. 33, no. 9, pp. 1821–1830, 2023, doi:10.1111/sms.14408 .

E. Yigitbas, M. Schmidt, A. Bucchiarone, S. Gottschalk, and G. Engels, “GaMoVR: Gamification-Based UML Learning Environment in Virtual Reality,” Science of Computer Programming, 2023.

C. Soyka, M. Ullrich, M. Striewe, and N. Schaper, “Comparison of Required Competences and Task Material in Modeling Education,”10.18417/EMISA.18.7__Enterprise Modelling and Information Systems Architectures, vol. 18, Art. no. 7, 2023, doi:10.18417/EMISA.18.7 .

M. Ott, N. Meihöfener, and I. Mozgova, “Methodical Approach to Reducing Design Time by using Neural Networks in Early Stages of Concept Development,” in Proceedings of the 34rd Annual International Solid Freeform Fabrication Symposium 2023, Austin, Texas, United States, 2023.

L. Margraf, D. Krause, and M. Weigelt, “Frontal theta reveals further information about neural valencedependent processing of augmented feedback in extensive motor practice - A secondary analysis,”10.1111/ejn.15951__European Journal of Neuroscience, vol. 57, no. 8, pp. 1297–1316, 2023, doi:10.1111/ejn.15951 .

M. Weigelt, D. Krause, and I. Güldenpenning, “Learning and Memory in Sports,” in Sport and Exercise Psychology, J. Schüler, M. Wegner, H. Plessner, and R. C. Eklund, Eds. Champaign: Springer, 2023, pp. 41–70.

G. Jonas-Ahrend, P. Fraser-Abder, M. Kapanadze, F. Joubran, and A. Mazzolini, “Lessons learned from a global review study of physics textbook evaluation and its implications for teaching and learning in the classroom,” presented at the International Consortium of Research on Science and Mathematics Education, Panama City/Panama, 2023.