41 to 50 of 201 Results
Mar 6, 2023 - SFB-TRR 161 A03 "Quantification of Visual Analytics Transformations and Mappings"
Pomerenke, David; Dennig, Frederik L.; Keim, Daniel; Fuchs, Johannes; Blumenschein, Michael, 2022, "Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"", https://doi.org/10.18419/darus-3060, DaRUS, V2, UNF:6:UBKuKSiQ9Yl4rH7r00rY3g== [fileUNF]
This is the replication data for our publication "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters." It contains the datasets and the code used to render optimized Parallel Coordinate Plots. We used the following 36 datasets for ou... |
Feb 24, 2023 - Perceptual User Interfaces
Bulling, Andreas, 2023, "MPIIEmo", https://doi.org/10.18419/darus-3287, DaRUS, V1
We present a human-validated dataset that contains 224 high-resolution, multi-view video clips and audio recordings of emotionally charged interactions between eight couples of actors. The dataset is fully annotated with categorical labels for four basic emotions (anger, happines... |
Feb 20, 2023 - PN 6
Zaverkin, Viktor; Holzmüller, David; Bonfirraro, Luca; Kästner, Johannes, 2023, "Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials", https://doi.org/10.18419/darus-3299, DaRUS, V1
Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach. Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found on GitLab. The data represents TensorFlow v2 checkpoint... |
Kohlhaas, Rebecca; Kröker, Ilja; Oladyshkin, Sergey; Nowak, Wolfgang, 2023, "Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator", https://doi.org/10.18419/darus-2829, DaRUS, V1
This folder contains the code for the aMR-PC toolbox by Ilja Kröker in the version used for the code in GALMAP_code. This toolbox was also used for Kröker et al. 2022 Link to current version of the toolbox here Data This folder contains inputs and simulated outputs of the CO_2 be... |
Feb 14, 2023 - Institute for Theoretical Physics III: Büchler Group
Ilg, Tobias; Büchler, Hans Peter, 2023, "Data for "Ground-state stability and excitation spectrum of a one-dimensional dipolar supersolid"", https://doi.org/10.18419/darus-3295, DaRUS, V1
Mathematica file and dataset to reproduce the results in "Ground-state stability and excitation spectrum of a one-dimensional dipolar supersolid". The Mathematica file "Groundstatestabiity.nb" created with Mathematica 12.0.0.0 contains all relevant functions and descriptions to r... |
Feb 13, 2023 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media
Keim, Leon; Class, Holger; Schirmer, Larissa; Strauch, Bettina; Wendel, Kai; Zimmer, Martin, 2023, "Code for: Seasonal Dynamics of Gaseous CO2 Concentrations in a Karst Cave Correspond With Aqueous Concentrations in a Stagnant Water Column", https://doi.org/10.18419/darus-3276, DaRUS, V1
This dataset contains the DuMux code for the simulations in https://doi.org/10.3390/geosciences13020051 For the detailed list of software used, please have a look at the file install_class2023.sh. To run the simulations at your own computer, please conduct the following steps: In... |
Feb 13, 2023 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media
Keim, Leon; Class, Holger; Schirmer, Larissa; Wendel, Kai; Strauch, Bettina; Zimmer, Martin, 2023, "Data for: Measurement Campaign of Gaseous CO2 Concentrations in a Karst Cave with Aqueous Concentrations in a Stagnant Water Column 2021-2022.", https://doi.org/10.18419/darus-3271, DaRUS, V1
This dataset contains data generated during the measurement campaign inside the karst cave. The CO2 sensors in the cave air will continue to measure (as of Feb. 2023). For details on the site etc. see https://doi.org/10.3390/geosciences13020051 To create the graphs in the Class e... |
Feb 7, 2023 - Publication: Machine learning assists in increasing the time resolution of X-ray tomography
Lee, Dongwon; Steeb, Holger, 2023, "Image enhancement code: time-resolved tomograms of EICP application using 3D U-net", https://doi.org/10.18419/darus-2991, DaRUS, V1
This dataset contains the codes to reproduce the results of "Time resolved micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in sintered glass bead columns", cf. https://doi.org/10.18419/darus-2227. The code takes "low-dose" images as an input where the ima... |
Feb 3, 2023 - Institute for Structural Mechanics
Müller, Alexander, 2023, "Thin cylindrical magnetic nanodots revisited: Scripts and data", https://doi.org/10.18419/darus-3103, DaRUS, V1
This data set includes a Maple file, the data for the figures in the cited work and a C++ project for minizing the micromagnetic energy for the micromagnetic vortex mode. The Maple file contains the analytic derivation of the demagnetization energy for an in-plane single domain s... |
Feb 2, 2023 - SusI Final Workshop
Gläser, Dennis; Seeland, Anett; Schulze, Katharina; Burbulla, Samuel, 2023, "Verification benchmarks for single-phase flow in three-dimensional fractured porous media: DuMuX source code", https://doi.org/10.18419/darus-3228, DaRUS, V1
This dataset contains the source code for simulating the benchmark cases of Berre et al. (2021) with the open-source simulator DuMuX. The benchmarks focus on flow and transport through fractured porous media, considering fracture networks of varying complexity. The code in this d... |
