L. Werneck, E. Yildiz, M. Han, M. Keip, M. Sitti, and M. Ortiz. Software, (2023)Related to: Werneck, L., Han, M., Yildiz, E., Keip, M.-A., Sitti, M., & Ortiz, M. (2023). A Simple Quantitative Model of Neuromodulation, Part I: Ion Flow Through Neural Ion Channels. Journal of the Mechanics and Physics of Solids, 182:105457. doi: 10.1016/j.jmps.2023.105457.
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, and M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks.
T. Praditia. Dataset, (2020)Related to: Praditia, T., Walser, T., Oladyshkin, S. and Nowak, W.: Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies 2020.
J. Magiera. Dataset, (2024)Related to: Jim Magiera, Deep Ray, Jan S. Hesthaven, Christian Rohde, Constraint-aware neural networks for Riemann problems, Journal of Computational Physics, Volume 409, 2020, 109345. doi: 10.1016/j.jcp.2020.109345.
P. Reiser, J. Aguilar, A. Guthke, and P. Bürkner. Software, (2024)Related to: Reiser P., Aguilar J. E., Guthke A., & Bürkner P. C. (2023). Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. ArXiv preprint 2312.05153. arXiv: 2312.05153.
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.
M. Alvarez Chaves, H. Gupta, U. Ehret, and A. Guthke. Software, (2024)Related to: Álvarez Chaves, Manuel, Gupta, Hoshin V., Ehret, Uwe and Guthke, Anneli. On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data. Entropy 2024, 26(5), 387. doi: 10.3390/e26050387.
A. Schlaich. Dataset, (2023)Related to: The possible role of lipid bilayer properties in the evolutionary disappearance of betaine lipids in seed plants. Bolik Stéphanie, Schlaich Alexander, Mukhina Tetiana, Amato Alberto, Bastien Olivier, Schneck Emanuel, Demé Bruno, Jouhet Juliette. bioRxiv 2023.01.24.525350. doi: 10.1101/2023.01.24.525350.
S. Hermann. Dataset, (2022)Related to: Hermann, S., Fehr, J. Documenting research software in engineering science. Sci Rep 12, 6567 (2022). doi: 10.1038/s41598-022-10376-9.
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.
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.
J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
P. Santana Chacon, M. Hammer, I. Wochner, J. Walter, and S. Schmitt. Software, (2023)Related to: P. F. S. Chacon, M. Hammer, I. Wochner, J. R. Walter and S. Schmitt. A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers. doi: 10.1080/10255842.2023.2293652.
R. Skukies. Software, (2023)Related to: Skukies, R., & Ehinger, B. V. (2023). The effect of estimation time window length on overlap correction in EEG data (2023.06.05.543689). bioRxiv. doi: 10.1101/2023.06.05.543689.
