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.
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.
D. Holzmüller, L. Grinsztajn, and I. Steinwart. Software, (2024)Related to: David Holzmüller, Léo Grinsztajn, and Ingo Steinwart. Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data, 2024. arXiv: 2407.04491.
S. Reuschen, T. Xu, and W. Nowak. Dataset, (2020)Related to: Reuschen, S., Xu, T., Nowak, W., 2020. Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC. Advances in Water Resources 141, 103614. doi: 10.1016/j.advwatres.2020.103614.
L. Scholz, and C. Bringedal. Dataset, (2021)Related to: Scholz, L., Bringedal, C. A Three-Dimensional Homogenization Approach for Effective Heat Transport in Thin Porous Media. Transp Porous Med (2022). doi: 10.1007/s11242-022-01746-y.
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".
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.
L. Keim, H. Class, L. Schirmer, B. Strauch, K. Wendel, and M. Zimmer. Dataset, (2023)Related to: Class, H.; Keim, L.; Schirmer, L.; Strauch, B.; Wendel, K.; Zimmer, M. Seasonal Dynamics of Gaseous CO2 Concentrations in a Karst Cave Correspond with Aqueous Concentrations in a Stagnant Water Column. Geosciences 2023, 13, 51. doi: 10.3390/geosciences13020051.
L. Kloker, and C. Bringedal. Dataset, (2022)Related to: Leon H. Kloker and Carina Bringedal, Solution approaches for evaporation-driven density instabilities in a slab of saturated porous media, Physics of Fluids 34, 096606 (2022). doi: 10.1063/5.0110129.
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.
H. Dobbertin, R. Löw, and S. Scheel. Physical review. A, covering atomic, molecular, and optical physics and quantum information, 102 (3):
031701(2020)
N. Rodrigues, F. Dennig, V. Brandt, D. Keim, and D. Weiskopf. Software, (2024)Related to: Rodrigues, N., Dennig, F. L., Brandt, V., Keim, D. A., & Weiskopf, D. (2024). Comparative Evaluation of Animated Scatter Plot Transitions. arXiv preprint. arXiv: 2401.04692.
T. Munz, N. Schäfer, T. Blascheck, K. Kurzhals, E. Zhang, and D. Weiskopf. VINCI '20: Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, page 11. Association for Computing Machinery, (2020)
A. Streichert, K. Angerbauer, M. Schwarzl, and M. Sedlmair. ETRA '20 Short Papers : ACM Symposium on Eye Tracking Research and Applications, page 51. New York, Association for Computing Machinery, (2020)