M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, und 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. Hägele, T. Krake, und D. Weiskopf. Dataset, (2022)Related to: D. Hägele, T. Krake and D. Weiskopf, Üncertainty-Aware Multidimensional Scaling," in IEEE Transactions on Visualization and Computer Graphics, 2022. doi: 10.1109/TVCG.2022.3209420.
J. Hommel, und L. Gehring. Dataset, (2022)Related to: Hommel, J., Gehring, L., Weinhardt, F., Ruf, M., & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Gültig, J. Range, B. Schmitz, und 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, und 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.
T. Munz, D. Väth, P. Kuznecov, N. Vu, und 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, und 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.
T. Krake, D. Klötzl, B. Eberhardt, und D. Weiskopf. Software, (2022)Related to: Tim Krake, Daniel Klötzl, Bernhard Eberhardt and Daniel Weiskopf, "Constrained Dynamic Mode Decomposition", in IEEE Transactions on Visualization and Computer Graphics, 2022. doi: 10.1109/TVCG.2022.3209437.
I. Banerjee, und 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.
B. Ceranski, D. Fritsch, G. Mammadov, M. Niklaus, T. Schweizer, S. Simon, J. Wagner, und K. Zhan. Dataset, (2022)Related to: FRITSCH, Dieter ; WAGNER, Jörg F ; CERANSKI, Beate ; SIMON, Sven ; NIKLAUS, Maria ; ZHAN, Kun ; MAMMADOV, Gasim: Making Historical Gyroscopes Alive—2D and 3D Preservations by Sensor Fusion and Open Data Access. In: Sensors, 21 (2021), Nr. 3, S. 957. doi: 10.3390/s21030957.
B. Ceranski, D. Fritsch, G. Mammadov, M. Niklaus, T. Schweizer, S. Simon, J. Wagner, und K. Zhan. Dataset, (2022)Related to: FRITSCH, Dieter ; WAGNER, Jörg F ; CERANSKI, Beate ; SIMON, Sven ; NIKLAUS, Maria ; ZHAN, Kun ; MAMMADOV, Gasim: Making Historical Gyroscopes Alive—2D and 3D Preservations by Sensor Fusion and Open Data Access. In: Sensors, 21 (2021), Nr. 3, S. 957. doi: 10.3390/s21030957.
J. Gärtner. Software, (2022)Related to: D. Dietzel, "Modeling and simulation of flash-boiling of cryogenic liquids", PhD Thesis, University of Stuttgart, 2020. doi: 10.18419/opus-10974.
D. Holzmüller, V. Zaverkin, J. Kästner, und 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.
S. Vahid Dastjerdi, N. Karadimitriou, und 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.
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.
E. Vecchi, N. Falk, I. Jundi, und G. Lapesa. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 1, Seite 1338-1352. Stroudsburg, Association for Computational Linguistics, (2021)