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21 to 30 of 30 Results
Jul 1, 2023 - Usability and Sustainability of Simulation Software
Schrader, Timo Pierre; Schneider, David; Uekermann, Benjamin, 2023, "Replication Data for: Data-Parallel Radial-Basis Function Interpolation in preCICE", https://doi.org/10.18419/darus-3574, DaRUS, V1
This dataset contains setup and result files for the performance measurements presented in Schneider et al. "Data-Parallel Radial-Basis Function Interpolation in preCICE". Furthermore, it contains the used snapshot of preCICE, ASTE, and Gingko. See the README for information on h...
Jun 20, 2023 - Usability and Sustainability of Simulation Software
Willeke, Leonard; Schneider, David; Uekermann, Benjamin, 2023, "Reproduction data for: A preCICE-FMI Runner to Couple FMUs to PDE-Based Simulations", https://doi.org/10.18419/darus-3549, DaRUS, V1
Input files and results for two simulation examples using the preCICE-FMI runner as described in "A preCICE-FMI Runner to Couple FMUs to PDE-Based Simulations". First, the simulation of a partitioned mass-spring oscillator system is considered. All model equations are based on OD...
Jun 7, 2023 - Usability and Sustainability of Simulation Software
Willeke, Leonard, 2023, "Replication Data for: A preCICE-FMI Runner to couple controller models to PDEs", https://doi.org/10.18419/darus-3408, DaRUS, V1
A preCICE-FMI Runner was developed during the Master's Thesis "A preCICE-FMI Runner to couple controller models to PDEs". It couples models using the FMI standard with other simulation programs via the coupling library preCICE. This data set contains the code and casefiles presen...
Jun 6, 2023 - Projects without PN Affiliation
Herkert, Robin, 2023, "Replication Code for: Randomized Symplectic Model Order Reduction for Hamiltonian Systems", https://doi.org/10.18419/darus-3519, DaRUS, V1
This dataset includes the code to reproduce the results from the paper titled "Randomized Symplectic Model Order Reduction for Hamiltonian Systems". In this paper randomized symplectic basis generation techniques are introduced. The numerical experiments where error decay rates a...
Jun 5, 2023 - Usability and Sustainability of Simulation Software
Schrader, Timo Pierre, 2023, "Replication Data for: Efficient Application of Accelerator Cards for the Coupling Library preCICE", https://doi.org/10.18419/darus-3404, DaRUS, V1
This dataset contains all testcase setup files and result files for the measurements presented in the Master's thesis with the title "Efficient Application of Accelerator Cards for the Coupling Library preCICE" (Author: Timo Pierre Schrader). Furthermore, it contains the version...
May 25, 2023 - Data and Code for: Meta-Uncertainty in Bayesian Model Comparison
Schmitt, Marvin, 2023, "Replication Code for: Meta-Uncertainty in Bayesian Model Comparison", https://doi.org/10.18419/darus-3514, DaRUS, V1, UNF:6:zUDr3KGdcaDCy+jFtcz8lA== [fileUNF]
This dataverse contains the code for the paper Meta-Uncertainty in Bayesian Model Comparison: https://doi.org/10.48550/arXiv.2210.07278 Note that the R code is structured as a package, thus requiring a local installation with subsequent loading via library(MetaUncertaintyPaper)....
May 15, 2023 - PN 4-7
Baier, Alexandra; Frank, Daniel, 2023, "deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning", https://doi.org/10.18419/darus-3455, DaRUS, V1
deepsysid is a system identification toolkit for multistep prediction using deep learning and hybrid methods. The toolkit is easy to use. After you follow the instructions in the README, you will be able to download a dataset, run hyperparameter optimization and identify your bes...
May 15, 2023 - PN 4-7
Baier, Alexandra; Aspandi, Decky; Staab, Steffen, 2023, "Supplements for "ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks""", https://doi.org/10.18419/darus-3457, DaRUS, V1
This repository contains the necessary scripts to reproduce the results from our paper "ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks". See the README file for more information. The most current version of this software is a...
May 2, 2023 - DuMux
Oukili, Hamza; Ackermann, Sina; Buntic, Ivan; Class, Holger; Coltman, Edward; Flemisch, Bernd; Ghosh, Tufan; Gläser, Dennis; Grüninger, Christoph; Hommel, Johannes; Jupe, Tim; Keim, Leon; Kelm, Mathis; Kiemle, Stefanie; Koch, Timo; Kostelecky, Anna Mareike; Pallam, Harsha Vardhan; Schneider, Martin; Stadler, Leopold; Utz, Martin; Wang, Yue; Wendel, Kai; Winter, Roman; Wu, Hanchuan, 2023, "DuMux 3.7.0", https://doi.org/10.18419/darus-3405, DaRUS, V1
Release 3.7.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environmen...
Apr 5, 2023 - PN 6
Holzmüller, David; Zaverkin, Viktor; Kästner, Johannes; Steinwart, Ingo, 2023, "Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]", https://doi.org/10.18419/darus-3394, DaRUS, V1
This dataset contains code and data for the third arXiv version of our paper "A Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Act...
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