J. Finkbeiner, S. Tovey, and C. Holm. Dataset, (2024)Related to: Jan Finkbeiner, Samuel Tovey, Christian Holm: Generating Minimal Training Sets for Machine Learned Potentials (2023). arXiv: 2309.03840.
A. Baier, D. Aspandi Latif, and S. Staab. Software, (2023)Related to: Alexandra Baier, Decky Aspandi and Steffen Staab, "ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks", Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23), 2023.
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.
R. Herkert. Software, (2024)Related to: R. Herkert, P. Buchfink, T. Wenzel, B. Haasdonk, P. Toktaliev, O. Iliev (2024), "Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data". arXiv: 2405.19170.
M. Ruf, and H. Steeb. Dataset, (2021)Related to: Ruf, M., & Steeb, H. (2022). Effects of thermal treatment on acoustic waves in Carrara marble. International Journal of Rock Mechanics and Mining Sciences, 159, 105205. doi: 10.1016/j.ijrmms.2022.105205.
M. Ruf, and H. Steeb. Dataset, (2020)Related to: Lissa, S.; Ruf, M.; Steeb, H. & Quintal, B. (2020). Effects of crack roughness on attenuation caused by squirt flow in Carrara marble. SEG Technical Program Expanded Abstracts 2020, 2439-2443. doi: 10.1190/segam2020-3427789.1.
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.
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.
M. Ruf, K. Taghizadeh Bajgirani, and H. Steeb. Dataset, (2023)Related to: Taghizadeh, K., Ruf, M., Luding, S., & Steeb, H. (2023). X-ray 3D imaging–based microunderstanding of granular mixtures: Stiffness enhancement by adding small fractions of soft particles. Proceedings of the National Academy of Sciences, 120(26), e2219999120. doi: 10.1073/pnas.2219999120.
N. Schäfer, P. Tilli, T. Munz-Körner, S. Künzel, S. Vidyapu, N. Vu, and D. Weiskopf. Software, (2023)Related to: N. Schäfer, S. Künzel, T. Munz, P. Tilli, N. T. Vu, and D. Weiskopf. Visual Analysis of Scene-Graph-Based Visual Question Answering. Proceedings of the 16th International Symposium on Visual Information Communication and Interaction (VINCI 2023). 2023.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: González, B., Calvar, N., Gómez, E., & Domínguez, Á. (2007). Density, dynamic viscosity, and derived properties of binary mixtures of methanol or ethanol with water, ethyl acetate, and methyl acetate at T=(293.15, 298.15, and 303.15)K. The Journal of Chemical Thermodynamics, 39(12), 1578-1588. doi: 10.1016/j.jct.2007.05.004.
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.
I. Banerjee, and P. Walter. Dataset, (2022)Related to: Banerjee, I., Walter, P., Guthke, A., Mumford, K.G. & Nowak, W. (2022). The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence. Computational Geosciences. Accepted for publication.
D. Fauser, and H. Steeb. Dataset, (2021)Related to: Fauser, Dominik; Steeb, Holger (2022) "Influence of humidity on the rheology of thermoresponsive shape memory polymers", Journal of Materials Science 57, 9508-9524. doi: 10.1007/s10853-022-07206-8.
T. Munz, D. Väth, P. Kuznecov, N. Vu, and D. Weiskopf. Software, (2022)Related to: T. Munz, D. Väth, P. Kuznecov, N. T. Vu, and D. Weiskopf. "Visualization-based improvement of neural machine translation", Computers & Graphics, 2021. doi: 10.1016/j.cag.2021.12.003.
V. Zaverkin, D. Holzmüller, I. Steinwart, and J. Kästner. Software, (2021)Related to: V. Zaverkin, D. Holzmüller, I. Steinwart, and J. Kästner, “Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments,” J. Chem. Theory Comput. 17, 6658–6670 (2021). doi: 10.1021/acs.jctc.1c00527.