D. Holzmüller, V. Zaverkin, J. Kästner, and I. Steinwart. Software, (2022)Related to: David, Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2022. arXiv: 2203.09410.
A. Gonzalez-Nicolas Alvarez. Software, (2021)Related to: Gonzalez-Nicolas, A.; Schwientek, M.; Sinsbeck, M; Nowak, W. Characterization of export regimes in concentration-discharge plots via an advanced time-series model and event-based sampling strategies. Water 2021, 13, 1723. doi: 10.3390/w13131723.
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.
R. Herkert. Software, (2024)Related to: R. Herkert, P. Buchfink, B. Haasdonk, J. Rettberg, J. Fehr. (2024), "Error Analysis of Randomized Symplectic Model Order Reduction for Hamiltonian systems". arXiv: 2405.10465.
J. Kneifl, and J. Fehr. Software, (2020)Related to: Jonas Kneifl, Dennis Grunert, and Joerg Fehr (2021). A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning. In: International Journal for Numerical Methods in Engineering, 122:4774-4786. doi: 10.1002/nme.6712.
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.
D. Holzmüller, V. Zaverkin, J. Kästner, and I. Steinwart. Software, (2023)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410.
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.
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.
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.
M. Ruf, M. Balcewicz, E. Saenger, and H. Steeb. Dataset, (2021)Related to: Balcewicz, M., Siegert, M., Gurris, M., Ruf, M., Krach, D., Steeb, H., & Saenger, E.H. (2021). Digital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone. Frontiers in Earth Science (under review).
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.
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.
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. 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.
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. 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.
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.
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.
L. Nölle, P. Lerge, O. Martynenko, I. Wochner, F. Kempter, C. Kleinbach, S. Schmitt, and J. Fehr. Dataset, (2022)Related to: Kleinbach, C., Martynenko, O., Promies, J., Haeufle, D.F., Fehr, J., Schmitt, S., 2017. Implementation and validation of the extended hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models. Biomedical engineering online 16, 109. doi: 10.1186/s12938-017-0399-7.
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. Rosenfelder, H. Ebel, and P. Eberhard. Dataset, (2023)Related to: Rosenfelder, M., Ebel, H., Eberhard, P. (2023). Force-based organization and control scheme for the non-prehensile cooperative transportation of objects. Robotica, pp. 1-14, 2023. doi: 10.1017/S0263574723001704.
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. Balcewicz, M. Ruf, H. Steeb, and E. Saenger. Dataset, (2021)Related to: Balcewicz, M., Siegert, M., Gurris, M., Ruf, M., Krach, D., Steeb, H., & Saenger, E.H. (2021). Digital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone. Frontiers in Earth Science (under review).
J. Yang, S. Kondrat, C. Lian, H. Liu, A. Schlaich, and C. Holm. Dataset, (2023)Related to: J. Yang, S. Kondrat, C. Lian, H. Liu, A. Schlaich, und C. Holm, „Solvent Effects on Structure and Screening in Confined Electrolytes“, Phys. Rev. Lett., Bd. 131, Nr. 11, 118201, Sep. 2023. doi: 10.1103/PhysRevLett.131.118201.
F. Huber, P. Bürkner, D. Göddeke, and M. Schulte. Dataset, (2023)Related to: Huber, Felix; Bürkner, Paul-Christian; Göddeke, Dominik; Schulte, MiriamKnowledge-Based Modeling of Simulation Behavior for Bayesian OptimizationComputational Mechanics (submitted).
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.
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.
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. 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.
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.
M. Ruf, J. Hommel, and H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Ruf, K. Taghizadeh Bajgirani, and H. Steeb. Dataset, (2021)Related to: Ruf, M., Taghizadeh, K. & Steeb, H. (2022). Multi-scale characterization of granular media by in situ laboratory X-ray computed tomography. GAMM Mitteilungen, 45(3-4), e202200011. doi: 10.1002/gamm.202200011.
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.
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.
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).
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. Ruf, J. Hommel, and H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
S. Vahid Dastjerdi, N. Karadimitriou, and H. Steeb. Dataset, (2022)Related to: Vahid Dastjerdi, S.; Karadimitriou, N.; Hassanizadeh, S. M. & Steeb, H.: Experimental evaluation of fluid connectivity in two-phase flow in porous media. Advances in Water Resources 172 (2023), 104378. doi: 10.1016/j.advwatres.2023.104378.
M. Ruf, J. Hommel, and H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
D. Fauser, M. Kuhn, 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).
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.
X. Xu. Dataset, (2023)Related to: Xu, Xiang, Xi Zhang, Andrei Ruban, Siegfried Schmauder, and Blazej Grabowski. "Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al." Acta Materialia 255 (2023): 118986. doi: 10.1016/j.actamat.2023.118986.
M. Balcewicz, M. Ruf, H. Steeb, and E. Saenger. Dataset, (2021)Related to: Balcewicz, M., Siegert, M., Gurris, M., Ruf, M., Krach, D., Steeb, H., & Saenger, E.H. (2021). Digital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone. Frontiers in Earth Science (under review).
M. Steffen. Dataset, (2023)Related to: Maier, S.: Simulation of a Novel Restraint Safety Concept for Motorcycles, Dissertation, University of Stuttgart, Shaker Verlag, Aachen, tbd.
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.
T. Giess, S. Itzigehl, J. Range, J. Bruckner, and J. Pleiss. Dataset, (2022)Related to: Giess T., Itzigehl S., Range J. P., Bruckner J. R., Pleiss J., FAIR and scalable management of small-angle X-ray scattering data, 2023. doi: 10.1107/S1600576723001577.
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.
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.
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.
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.
S. Schulz, C. Bringedal, and S. Ackermann. Dataset, (2021)Related to: SimTech Project work "Herleitung reduzierter Modelle einer Zweiphasenströmung zwischen parallelen Platten mit Slip-Bedingungen".
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.
S. Vahid Dastjerdi, H. Steeb, M. Ruf, D. Lee, F. Weinhardt, N. Karadimitriou, and H. Class. Dataset, (2021)Related to: Weinhart, 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. Water Resources Research, Technical Reports: Methods. doi: 10.1029/2020WR029361.
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.
A. Schlaich. Dataset, (2021)Related to: Schlaich, A., Jin, D., Bocquet, L. & Coasne, B. (2021). Wetting transition of ionic liquids at metal surfaces: A computational molecular approach to electronic screening using a virtual Thomas-Fermi fluid. arXiv: 2002.11526.
A. Gonzalez-Nicolas Alvarez. Dataset, (2021)Related to: Gonzalez-Nicolas, A.; Schwientek, M.; Sinsbeck, M; Nowak, W. Characterization of export regimes in concentration-discharge plots via an advanced time-series model and event-based sampling strategies. Water 2021, 13, 1723. doi: 10.3390/w13131723.
F. Weinhardt, J. Deng, H. Steeb, and H. Class. Dataset, (2022)Related to: Weinhardt, F.; Deng, J.; Hommel, J.; Vahid Dastjerdi, S.; Gerlach, R.; Steeb, H.; Class, H. (2022). Spatiotemporal Distribution of Precipitates and Mineral Phase Transition During Biomineralization Affect Porosity–Permeability Relationships. Transport in Porous Media 143, 527–549 (2022). doi: 10.1007/s11242-022-01782-8.
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. 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. arXiv: 2210.07182.
T. Siebert, N. Stutzig, J. Fehr, C. Holzapfel, S. Hunger, L. Broß, and M. Millard. dvs-Biomechanik 2023 Tagungsband : Beiträge zur Tagung der dvs-Sektion Biomechanik 2023 an der Otto-von-Guericke-Universität Magdeburg, page 180-182. Stuttgart, Steinbeis-Edition, (2023)
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.
P. Stärk, and A. Schlaich. Software, (2024)Related to: Artemov, V.; Frank, L.; Doronin, R.; Stärk, P.; Schlaich, A.; Andreev, A.; Leisner, T.; Radenovic, A.; Kiselev, A. The Three-Phase Contact Potential Difference Modulates the Water Surface Charge. J. Phys. Chem. Lett. 2023, 14, 4796-4802. doi: 10.1021/acs.jpclett.3c00479.
A. Singha Hazari, S. Chandra, Q. Song, D. Hunger, N. Neuman, J. Slageren, E. Klemm, B. Sarkar, and S. Kar. Dataset, (2024)Related to: Chandra, S., Singha Hazari, A., Song, Q., Hunger, D., Neuman, N. I., van Slageren, J., Klemm, E. & Sarkar, B. (2023). Remarkable Enhancement of Catalytic Activity of Cu-Complexes in the Electrochemical Hydrogen Evolution Reaction by Using Triply Fused Porphyrin. ChemSusChem 16, e202201146. doi: 10.1002/cssc.202201146.
M. Raff, and D. Remy. Dataset, (2024)Related to: M. Raff, N. Rosa and C. D. Remy, "Connecting Gaits in Energetically Conservative Legged Systems," in IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 8407-8414, July 2022,. doi: 10.1109/LRA.2022.3186500.
K. Abitaev, Y. Qawasmi, P. Atanasova, C. Dargel, T. Hellweg, and T. Sottmann. Dataset, (2024)Related to: Abitaev, Karina; Qawasmi, Yaseen; Atanasova, Petia; Dargel, Carina; Bill, Joachim; Hellweg, Thomas; Sottmann, Thomas: Adjustable polystyrene nanoparticle templates for the production of mesoporous foams and ZnO inverse opals. In: Colloid and Polymer Science 299 (2021), 243-258. doi: 10.1007/s00396-020-04791-5.
G. Tkachev, R. Cutura, M. Sedlmair, S. Frey, and T. Ertl. CHI EA '22 : Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, page 10. New York, Association for Computing Machinery, (2022)