K. Taghizadeh, M. Ruf, S. Luding, and H. Steeb. Proceedings of the National Academy of Sciences of the United States of America, 120 (26):
e2219999120(2023)
M. Brunn, N. Himthani, G. Biros, M. Mehl, and A. Mang. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, page 38. Piscataway, IEEE, (2020)
R. Leiteritz, M. Hurler, and D. Pflüger. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), page 1668-1673. Piscataway, IEEE, (2021)
F. Black, P. Schulze, and B. Unger. Active Flow and Combustion Control 2021 : Papers Contributed to the Conference “Active Flow and Combustion Control 2021”, September 28-29, 2021, Berlin, Germany, 152, page 203-224. Cham, Springer, (2021)
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)
J. Schmalfuss, C. Riethmüller, M. Altenbernd, K. Weishaupt, and D. Göddeke. Presentations and Plenary videos to 9th edition of the International Conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED PROBLEMS 2021), Barcelona, Scipedia, S.L., (2021)
T. Munz, R. Garcia, and D. Weiskopf. Software, (2021)Related to: R. Garcia, T. Munz, and D. Weiskopf. "Visual Analytics Tool for the Interpretation of Hidden States in Recurrent Neural Networks". Visual Computing for Industry, Biomedicine, and Art (VCIBA). 2021. doi: 10.1186/s42492-021-00090-0.
H. Hsueh. Dataset, (2021)Related to: Han-Fang Hsueh, Anneli Guthke, Thomas Wöhling, Wolfgang Nowak: Diagnosis of model-structural errors with a sliding time-window Bayesian analysis. In: Water Resource Research (submitted). arXiv: 2107.09399.
G. Tkachev. Software, (2021)Related to: G. Tkachev, S. Frey and T. Ertl, "S4: Self-Supervised learning of Spatiotemporal Similarity," in IEEE Transactions on Visualization and Computer Graphics. doi: 10.1109/TVCG.2021.3101418.
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.
T. Munz, N. Schäfer, T. Blascheck, K. Kurzhals, E. Zhang, and D. Weiskopf. Software, (2020)Related to: T. Munz, N. Schäfer, T. Blascheck, K. Kurzhals, E. Zhang, and D. Weiskopf. "Comparative Visual Gaze Analysis for Virtual Board Games". Proceedings of the 13th International Symposium on Visual Information Communication and Interaction (VINCI 2020). 2020. DOI: 10.1145/3430036.3430038.
F. Weinhardt, H. Class, S. Vahid Dastjerdi, N. Karadimitriou, D. Lee, and H. Steeb. Dataset, (2021)Related to: Weinhardt, F.; Class, H.; Vahid Dastjerdi, S.; Karadimitriou, N.; Lee, D.; Steeb, H.(2021). Experimental Methods and Imaging for Enzymatically Induced Calcite Precipitation in a microfluidic cell. Accepted in Water Resources Research. doi: 10.1029/2020WR029361.
D. Fauser, and H. Steeb. Dataset, (2021)Related to: Fauser, Dominik; Steeb, Holger, (2021), "Influence of Humidity on the Rheology of Thermoresponsive Shape Memory Polymers", Journal of Materials Science (under review).
D. Holzmüller. Software, (2022)Related to: David Holzmüller and Dirk Pflüger. Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework. Sparse Grids and Applications - Munich 2018 (2021). doi: 10.1007/978-3-030-81362-8_4.
L. Schepp, B. Ahrens, M. Balcewicz, M. Duda, M. Nehler, M. Osorno, D. Uribe, H. Steeb, B. Nigon, F. Stöckhert and 5 other author(s). Dataset, (2020)Related to: Schepp, L.L., Ahrens, B., Balcewicz, M., Duda, M., Nehler, M., Osorno, M., Uribe, D., Steeb, S., Nigon, B., Stöckhert, F., Swanson, D.A., Siegert, M., Gurris, M. & Saenger, E.H. (2020). Digital rock physics and laboratory considerations on a high-porosity volcanic rock. Scientific Reports, 10, 5840. doi: 10.1038/s41598-020-62741-1.
M. Ruf, and H. Steeb. Dataset, (2020)Related to: Ruf, M., & Steeb, H. (2020). An open, modular, and flexible micro X-ray computed tomography system for research. Review of Scientific Instruments, 91(11), 113102. doi: 10.1063/5.0019541.
M. Ruf, and H. Steeb. Dataset, (2020)Related to: Ruf, M., & Steeb, H. (2020). An open, modular, and flexible micro X-ray computed tomography system for research. Review of Scientific Instruments, 91(11), 113102. doi: 10.1063/5.0019541.
M. Ruf, D. Lee, and H. Steeb. Dataset, (2023)Related to: Ruf, M., Lee, D., & Steeb, H. (2023). A multifunctional mechanical testing stage for micro X-ray computed tomography. Review of Scientific Instruments, 94, 085115. doi: 10.1063/5.0153042.
M. Ruf, and H. Steeb. Dataset, (2023)Related to: Ruf, M., Lee, D., & Steeb, H. (2023). A multifunctional mechanical testing stage for micro X-ray computed tomography. Review of Scientific Instruments, 94, 085115. doi: 10.1063/5.0153042.
D. Holzmüller. Software, (2021)Related to: David Holzmüller. On the Universality of the Double Descent Peak in Ridgeless Regression. International Conference on Learning Representations, 2021. arXiv: 2010.01851.
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.
J. Pelzer. Dataset, (2023)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.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Derlacki, Z. J., Easteal, A. J., Edge, A. V. J., Woolf, L. A., & Roksandic, Z. (1985). Diffusion coefficients of methanol and water and the mutual diffusion coefficient in methanol-water solutions at 278 and 298 K. The Journal of Physical Chemistry, 89(24), 5318-5322. doi: 10.1021/j100270a039.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: D’Errico, G., Ortona, O., Capuano, F., & Vitagliano, V. (2004). Diffusion Coefficients for the Binary System Glycerol + Water at 25 °C. A Velocity Correlation Study. Journal of Chemical & Engineering Data, 49(6), 1665-1670. doi: 10.1021/je049917u.
I. Banerjee. Dataset, (2021)Related to: Banerjee, I., Guthke, A., Van de Ven, C. J. C., Mumford, K. G. & Nowak, W. (2021). Overcoming the Model-Data-Fit Problem in Porous Media: A Quantitative Method to Compare Invasion-Percolation Models to High-Resolution Data. Water Resources Research, 57, e2021WR029986. doi: 10.1029/2021WR029986.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.