31 to 40 of 42 Results
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 26, 2023 - Materials Design
Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/darus-3516, DaRUS, V1
Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script f... |
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 12, 2023 - Materials Design
Forslund, Axel; Jung, Jong Hyun; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals", https://doi.org/10.18419/darus-3339, DaRUS, V1
Data for the publication Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals, Phys. Rev. B 107, 174309 (2023). This data set contains - the training sets (VAS... |
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... |
Steffen, Maier, 2023, "Registered Cars and Motorized Two- and Three-wheelers in Worldwide Countries", https://doi.org/10.18419/darus-3378, DaRUS, V1
Interactive plot of registered cars and motorized two- and three-wheelers in worldwide countries based the data set from the "WHO Global Status Report on Road Safety 2018" of the World Health Organization. |
Mar 9, 2023 - PN 3-11
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, 2023, "Supplementary material for 'Structural basis for ninjurin-1 mediated plasma membrane rupture in lytic cell death'", https://doi.org/10.18419/darus-3373, DaRUS, V1
Eukaryotic cells can undergo different forms of programmed cell death, many of which culminate in plasma membrane rupture (PMR) as the defining terminal event. PMR was long thought to be driven by osmotic pressure, until it was recently shown to be in many cases an active process... |
