1 to 10 of 2,192 Results
Mar 19, 2024 - Scientific Computing
Bantel, Linus; Domanski, Peter, 2024, "Quanser IP-02 Inverted Cartpole Measurement Data for Analysis and Offline RL", https://doi.org/10.18419/darus-4085, DaRUS, V1, UNF:6:8MdHTluRf6u9Vntb4fvs/g== [fileUNF]
Recorded Data of the Swingup Task on the Inverted Cartpole IP-02 by Quanser. State transitions are as following: (pos, pos_dot, phi, phi_dot, action) -> (pos_new, pos_dot_new, phi_new, phi_dot_new) Actions are discrete from 0 to 8, with 4 being the zero-action. I.e. 0 and 8 are f... |
Mar 19, 2024 - Institute for Stochastics and Applications
Höpfl, Sebastian, 2024, "Percentile Intervals in Bayesian Inference are Overconfident", https://doi.org/10.18419/darus-4068, DaRUS, V1
This dataset demonstrates the difference in calculating percentile Intervals as approximation for Highest Density Intervals (HDI) vs. Highest Posterior Density (HPD). This is demonstrated with extended partial liver resection data (ZeLeR-study, ethical vote: 2018-1246-Material).... |
Mar 15, 2024 - Ikarus
Müller, Alexander; Vinod Kumar Mitruka, Tarun Kumar Mitruka; Jakob, Henrik, 2024, "Ikarus v0.4", https://doi.org/10.18419/darus-3889, DaRUS, V1
Ikarus is a C++-based library with Python bindings (link to documentation) built to solve partial differential equations with the finite element method. The dataset under this DOI contains the current release (v0.4) of the library. This release not only focuses on refactoring var... |
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. |
Mar 14, 2024 - PN 6A-4
Alvarez Chaves, Manuel; Gupta, Hoshin; Ehret, Uwe; Guthke, Anneli, 2024, "Replication Data for: Evaluating Non-Parametric Methods in Information Theory", https://doi.org/10.18419/darus-4087, DaRUS, V1
Non-Parametric Estimation in Information Theory 1. Introduction This is a repository for our paper on: "Evaluating Density- and Nearest Neighbor-based Methods to Accurately Estimate Information-Theoretic Quantities from Multi-Dimensional Sample Data". The projects is organizes as... |
Mar 14, 2024 - HLRS-exaFOAM
Lesnik, Sergey; Rusche, Henrik, 2024, "exaFOAM Microbenchmark MB10 - ERCOFTAC conical diffuser LES", https://doi.org/10.18419/darus-3745, DaRUS, V1
This work is part of the exaFOAM project that aims to enable the open-source CFD software OpenFOAM to exploit massively parallel HPC architectures and overcome performance scaling bottlenecks. The ERCOFTAC conical diffuser is a challenging case for turbulence modeling since it op... |
Mar 14, 2024 - HLRS-exaFOAM
Lesnik, Sergey; Rusche, Henrik, 2024, "exaFOAM Microbenchmark MB11 - Pitz&Daily Combustor", https://doi.org/10.18419/darus-3744, DaRUS, V1
This work is part of the exaFOAM project that aims to enable the open-source CFD software OpenFOAM to exploit massively parallel HPC architectures and overcome performance scaling bottlenecks. The case is based on the experiment carried out by Pitz and Daily 1983, who measured a... |
Mar 14, 2024 - HLRS-exaFOAM
ESI-Group, 2024, "exaFOAM Industrial Benchmark B9 - DrivAer ExtAero derivative", https://doi.org/10.18419/darus-3737, DaRUS, V1
This case has been developed as part of the exaFOAM project that aims to enable the open-source CFD software OpenFOAM to exploit massively parallel HPC architectures and overcome performance scaling bottlenecks. This derivative of geometry, provided by the exaFOAM Stakeholder Aud... |
Mar 14, 2024 - HLRS-exaFOAM
ESI-Group, 2024, "exaFOAM Industrial Benchmark B7 - Aeroacoustics DrivAer derivative", https://doi.org/10.18419/darus-3736, DaRUS, V1
This case has been developed as is part of the exaFOAM project that aims to enable the open-source CFD software OpenFOAM to exploit massively parallel HPC architectures and overcome performance scaling bottlenecks. This industrial test case is of direct interest to Stakeholders G... |