C. Homs Pons, and R. Lautenschlager. Software, (2024)Related to: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models, submitted to GAMM Mitteilungen.
F. Bechler. Dataset, (2024)Related to: Related Publication: Bechler, F.: Enabling Holistic Vehicle Safety - Combined Knowledge and Information through a Graph-based Approach, Dissertation, University of Stuttgart, Shaker Verlag, Aachen, tbd.
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.
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.
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. 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.
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.
A. Schlaich. Software, (2024)Related to: Alexander Schlaich, Matthieu Vandamme, Marie Plazanet, Benoit Coasne, "Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials", (2024). arXiv: arXiv:2403.19812.
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.
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.
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.
H. Jäger. Software, (2023)Related to: Jäger, Henrik, Alexander Schlaich, Jie Yang, Cheng Lian, Svyatoslav Kondrat und Christian Holm. 2023. A screening of results on the decay length in concentrated electrolytes. Faraday Discussions. Faraday Discussions (Februar). doi: 10.1039/d3fd00043e.
J. Potyka, and K. Schulte. Dataset, (2023)Related to: Johanna Potyka and Kathrin Schulte: A volume of fluid method for three dimensional direct numerical simulations of immiscible droplet collisions, International Journal of Multiphase Flow, Volume 170, 2024, 104654. doi: 10.1016/j.ijmultiphaseflow.2023.104654.
M. Schmitt. Software, (2023)Related to: Schmitt, M., Radev, S. T., Bürkner, P.-C. (2023). Meta-Uncertainty in Bayesian Model Comparison. Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11-29, 2023.
J. Rettberg, D. Wittwar, P. Buchfink, A. Brauchler, P. Ziegler, J. Fehr, and B. Haasdonk. Dataset, (2023)Related to: Rettberg, J.; Wittwar, D.; Buchfink, P.; Brauchler, A.; Ziegler, P.; Fehr, J.; Haasdonk, B.: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar. Mathematical and Computer Modelling of Dynamical Systems, 2023. doi: 10.1080/13873954.2023.2173238.
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. 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.
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.
S. Gravelle, D. Beyer, M. Brito, A. Schlaich, and C. Holm. Software, (2023)Related to: Simon Gravelle, David Beyer, Mariano Brito, Alexander Schlaich, Christian Holm: Reconstruction of NMR Relaxation Rates from Coarse-Grained Polymer Simulations, ChemRxiv, 2022. Preprint. doi: 10.26434/chemrxiv-2022-f90tv-v2.
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.
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.
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.
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).
A. Baier, and D. Frank. Software, (2023)Related to: Baier, Alexandra, Boukhers, Zeyd, & Staab, Steffen (2021). Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction. ArXiv, abs/2103.06727. arXiv: abs/2103.06727.
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.
J. Wachlmayr, G. Fläschner, K. Pluhackova, W. Sandtner, C. Siligan, and A. Horner. Dataset, (2023)Related to: Wachlmayr, Johann; Fläschner, Gotthold; Pluhackova, Kristyna; Sandtner, Walter, Siliga, Christine; Horner, Andreas, "Entropic barrier of water permeation through single-file channels" Comms. Chem. 2023,. doi: 10.1038/s42004-023-00919-0.
F. Kempter, L. Lantella, N. Stutzig, J. Fehr, and T. Siebert. Software, (2023)Related to: Kempter, Fabian; Lantella, Lorena; Stutzig, Norman; Fehr, Jörg and Siebert, Tobias: Role of Rotated Head Postures on Volunteer Kinematics and Muscle Activity in Braking Scenarios Performed on a Driving Simulator, Annals of Biomedical Engineering , Vol. 51, No. 4 p. 771-782 2023. doi: 10.1007/s10439-022-03087-9.
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.
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.
I. Tischler, A. Schlaich, and C. Holm. Software, (2023)Related to: Ingo Tischler, Alexander Schlaich, Christian Holm. Disentanglement of Surface and Confinement Effects for Diene Metathesis in Mesoporous Confinement. ACS Omega 2023. doi: 10.1021/acsomega.3c06195.
J. Rettberg, D. Wittwar, and R. Herkert. Software, (2023)Related to: Rettberg, J.; Wittwar, D.; Buchfink, P.; Brauchler, A.; Ziegler, P.; Fehr, J.; Haasdonk, B.: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar. Mathematical and Computer Modelling of Dynamical Systems, 2023, Vol. 29, No. 1, 116-148. doi: 10.1080/13873954.2023.2173238.
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.
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.
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, 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.
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.
J. Potyka, K. Schulte, and C. Planchette. Dataset, (2023)Related to: Johanna Potyka, Kathrin Schulte and Carole Planchette; Liquid distribution after head-on separation of two colliding immiscible liquid droplets. Physics of Fluids, 2023; 35 (10): 102125. doi: 10.1063/5.0168080.
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.
T. Munz-Körner, S. Künzel, and D. Weiskopf. Dataset, (2023)Related to: T. Munz-Körner, S. Künzel, and D. Weiskopf. "Visual-Explainable AI: The Use Case of Language Models". International Conference on Data-Integrated Simulation Science (SimTech2023). 2023.
N. Schäfer, P. Tilli, T. Munz-Körner, S. Künzel, S. Vidyapu, N. Vu, and D. Weiskopf. Dataset, (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.
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.
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.
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.
R. Herkert. Software, (2023)Related to: R. Herkert, P. Buchfink, B. Haasdonk, J. Rettberg, J. Fehr: Randomized Symplectic Model Order Reduction for Hamiltonian Systemsm 2023. arXiv: 2303.04036.
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. 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.
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.
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.
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.
J. Kneifl, and J. Fehr. Software, (2023)Related to: Kneifl, J., Kutz, J. N., Brunton, S.L., Fehr, J.: Multi-Hierarchical Surrogate Learning of Structural Dynamical Systems Using Graph Convolutional Neural Networks. To be submitted (2023).
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.
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.
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.
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: 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.
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.
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. 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.
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, 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, 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.
I. Tischler, C. Holm, and A. Schlaich. Software, (2022)Related to: Tischler, I., Schlaich, A., Holm, C., The Presence of a Wall Enhances the Probability for Ring-Closing Metathesis: Insights from Classical Polymer Theory and Atomistic Simulations. Macromol. Theory Simul. 2021, 30, 2000076. doi: 10.1002/mats.202000076.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Mikhail, S. Z., & Kimel, W. R. (1961). Densities and Viscosities of Methanol-Water Mixtures. Journal of Chemical & Engineering Data, 6(4), 533-537. doi: 10.1021/je60011a015.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Segur, J. B., & Oberstar, H. E. (1951). Viscosity of Glycerol and Its Aqueous Solutions. Industrial & Engineering Chemistry, 43(9), 2117-2120. doi: 10.1021/ie50501a040.
M. Gültig, J. Range, B. Schmitz, and J. Pleiss. Software, (2022)Related to: Cristancho, D., Delgado, D., Martínez, F., Abolghassemi Fakhree, M. A., & Jouyban, A. (2011). Volumetric properties of glycerol + water mixtures at several temperatures and correlation with the Jouyban-Acree model. Revista Colombiana de Ciencias Químico Farmacéuticas, 40. 92-115.
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.
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.
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.
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.
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.
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.
M. Alkämper, and J. Magiera. Software, (2022)Related to: M. Alkämper, J. M. Magiera and C. Rohde, “An Interface Preserving Moving Mesh in Multiple Space Dimensions” (2021), submitted. arXiv: 2112.11956.
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. 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.
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.
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.
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.