M. Degen, J. Santos, K. Pluhackova, G. Cebrero, S. Ramos, G. Jankevicius, E. Hartenian, U. Guillerm, S. Mari, B. Kohl and 7 other author(s). Dataset, (2023)Related to: Degen, Morris; Santos, José Carlos; Pluhackova, Kristyna; Cebrero, Gonzalo; Ramos, Saray; Jankevicius, Gytis; Hartenian, Ella; Guillerm, Undina; Mari, Stefania A.; Kohl, Bastian; Müller, Daniel J.; Schanda, Paul; Maier, Timm; Perez, Camilo; Sieben, Christian; Broz, Petr; Hiller, Sebastian, "Structural basis for ninjurin-1 mediated plasma membrane rupture in lytic cell death", Nature 2023. doi: 10.1038/s41586-023-05991-z.
S. Gravelle, C. Holm, and A. Schlaich. Software, (2023)Related to: Simon Gravelle, Sabina Haber-Pohlmeier, Carlos Mattea, Siegfried Stapf, Christian Holm and Alexander Schlaich: NMR Investigation of Water in Salt Crusts: Insights from Experiments and Molecular Simulations, ChemRxiv, 2023. doi: 10.26434/chemrxiv-2023-6dml7.
S. Gravelle, C. Holm, and A. Schlaich. Software, (2023)Related to: Simon Gravelle, Sabina Haber-Pohlmeier, Carlos Mattea, Siegfried Stapf, Christian Holm and Alexander Schlaich: NMR Investigation of Water in Salt Crusts: Insights from Experiments and Molecular Simulations, ChemRxiv, 2023. doi: 10.26434/chemrxiv-2023-6dml7.
P. Kurzeja, and H. Steeb. Philosophical transactions of the Royal Society. Series A, Mathematical, physical and engineering sciences, 380 (2237):
20210370(2022)
J. Nicodemus, J. Kneifl, J. Fehr, and B. Unger. 10th Vienna International Conference on Mathematical Modelling MATHMOD 2022, 55, 20, page 331-336. Elsevier, (2022)
M. Kelm, C. Bringedal, and B. Flemisch. Dataset, (2023)Related to: Kelm, M., Gärttner, S., Bringedal, C. et al. Comparison study of phase-field and level-set method for three-phase systems including two minerals. Comput Geosci 26, 545-570 (2022). doi: 10.1007/s10596-022-10142-w.
V. Zaverkin, D. Holzmüller, L. Bonfirraro, and J. Kästner. Dataset, (2023)Related to: Viktor Zaverkin, David Holzmüller, Luca Bonfirraro, Johannes Kästner. Transfer learning for chemically accurate interatomic neural network potentials, Phys. Chem. Chem. Phys., 2023, 25, 5383-5396. doi: 10.1039/D2CP05793J.
J. Kneifl, D. Rosin, O. Avci, O. Röhrle, and J. Fehr. Software, (2023)Related to: Kneifl, J, Rosin, D., Röhrle, O., Fehr, J.: Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction, 2022. tbd.
M. Rosenfelder, H. Ebel, and P. Eberhard. Dataset, (2023)Related to: Rosenfelder, M., Ebel, H., Eberhard, P. (2023). A Force-Based Formation Synthesis Approach for the Cooperative Transportation of Objects. In: Petrič, T., Ude, A., Žlajpah, L. (eds) Advances in Service and Industrial Robotics. RAAD 2023. Mechanisms and Machine Science, vol 135. Springer, Cham. doi: 10.1007/978-3-031-32606-6_37.
P. Rodegast, S. Maier, J. Kneifl, and J. Fehr. Software, (2023)Related to: Rodegast, P., Maier, S., Kneifl, J., Fehr, J.: On using Machine Learning Algorithms for Motorcycle Collision Detection, 2023. tbd.
I. Wochner, and S. Schmitt. Software, (2022)Related to: Wochner, I., Schumacher, P., Martius, G., Büchler, D., Schmitt, S., & Haeufle, D. F. (2022). Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks. Conference on Robot Learning (CoRL) 2022. url: https://openreview.net/forum?id=Xo3eOibXCQ8.
R. Leiteritz, M. Hurler, and D. Pflüger. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), page 1668-1673. Piscataway, IEEE, (2021)
T. Praditia, M. Karlbauer, S. Otte, S. Oladyshkin, M. Butz, and W. Nowak. Dataset, (2022)Related to: Praditia, T., Karlbauer, M., Otte, S., Oladyshkin, S., Butz, M.V., Nowak, W.: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. Earth and Space Science Open Archive (2022). doi: 10.1002/essoar.10511934.1.