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Replication Code for: Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data
Jun 6, 2024 - Projects without PN Affiliation
Herkert, Robin, 2024, "Replication Code for: Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data", https://doi.org/10.18419/darus-4227, DaRUS, V1
This dataset includes the code to reproduce the results from the paper titled "Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data". In this paper we address the challenging application of 3D pore scale reactive flow under va...
Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Mar 14, 2024 - PN 2-7
Reiser, Philipp; Aguilar, Javier Enrique; Guthke, Anneli; Bürkner, Paul-Christian, 2024, "Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference", https://doi.org/10.18419/darus-4093, DaRUS, V1
This code allows to replicate key experiments from our paper: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. For further details, please refer to the README.md.
Replication Data for: Constraint-aware neural networks for Riemann problems
Jan 11, 2024 - Projects without PN Affiliation
Magiera, Jim M., 2024, "Replication Data for: Constraint-aware neural networks for Riemann problems", https://doi.org/10.18419/darus-3869, DaRUS, V1
Data sets of the article "Constraint-aware neural networks for Riemann problems", consisting of training and test data sets for Riemann solutions of the cubic flux model, an isothermal two-phase model, and the Euler equations for an ideal gas. You can find detailed information in...
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