DaRUS

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This is the Data Repository of the University of Stuttgart.

SFB 1313 "Interface-Driven Multi-Field Processes in Porous Media"

SFB 1333 "Molecular heterogeneous catalysis in confined geometries"

Institute of Biochemistry

Institute of Applied Mechanics (MIB)

Institute of Thermodynamics and Thermal Process Engineering

Stuttgart Center for Simulation Science (SC SimTech)

Cluster of Excellence Integrative Computational Design and Construction for Architecture (EXC IntCDC)

SFB/Transregio 161 "Quantitative Methods for Visual Computing"

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127,641 to 127,650 of 128,245 Results

SurfacesDistribution_perArea.h5 May 27, 2020 - Results and raw data of an adjustable similarity calculation for computer aided design (CAD) data Hierarchical Data Format - 7.6 MB - MD5: ffa2131039965828190032b9a2a944c9 CADDataHDF5 HDF5 table that contains the frequency of face categories per area of all bodies.
SurfacesDistribution_perNumber.h5 May 27, 2020 - Results and raw data of an adjustable similarity calculation for computer aided design (CAD) data Hierarchical Data Format - 7.9 MB - MD5: 58ef7641dfec007499d5a8b39623c5fa CADDataHDF5 HDF5 table that contains the frequency of face categories per number of faces of all bodies.
Dennis Zink(Universität Stuttgart) May 21, 2020CAD-CAM
CAD-CAM(Universität Stuttgart) May 21, 2020Institute of Aircraft Design
Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC May 19, 2020 - B04: Hybrid discrete-continuum models for fractured porous media: model choice and random field/network generation Reuschen, Sebastian; Xu, Teng; Nowak, Wolfgang, 2020, "Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC", https://doi.org/10.18419/DARUS-741, DaRUS, V1 This dataset contains the code and all relevant data and of the paper "Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC" by Sebastian Reuschen, Teng Xu and Wolfgang Nowak. Always cite the paper together with this dataset because this dataset is not self-explanatory. The code.tar.gz file conta...
code.tar.gz May 19, 2020 - Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC Gzip Archive - 143.7 KB - MD5: 434750ea8b39b02bc74c456d12660e5c
data.tar.gz May 19, 2020 - Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC Gzip Archive - 580.8 MB - MD5: 3a5ff7270f32fae9c2890e2c94837ec0
Glycoside Hydrolase 19 Engineering Database(Universität Stuttgart) May 18, 2020Bioinformatics Supporting information and original files for bioinformatic investigations using the Glycoside Hydrolase 19 Engineering Database (https://gh19ed.biocatnet.de/)
SFB-TRR 161 A02 "Quantifying Visual Computing Systems"(Universität Stuttgart) May 14, 2020SFB/Transregio 161 "Quantitative Methods for Visual Computing" The long-term goal of this project is to quantify visual computing systems, i.e.to assess, model and ultimately predict important characteristics that have a substantial impact on user experience.
SFB-TRR 161 INF "Collaboration Infrastructure"(Universität Stuttgart, Universität Konstanz) May 14, 2020SFB/Transregio 161 "Quantitative Methods for Visual Computing" Project INF supports the other projects of SFB/Transregio 161 by providing a central approach to data management and an infrastructure for virtual meetings in a large, high-resolution display scenario.

SurfacesDistribution_perArea.h5

May 27, 2020 - Results and raw data of an adjustable similarity calculation for computer aided design (CAD) data

Hierarchical Data Format - 7.6 MB -

CADDataHDF5

HDF5 table that contains the frequency of face categories per area of all bodies.

SurfacesDistribution_perNumber.h5

May 27, 2020 - Results and raw data of an adjustable similarity calculation for computer aided design (CAD) data

Hierarchical Data Format - 7.9 MB -

CADDataHDF5

HDF5 table that contains the frequency of face categories per number of faces of all bodies.

Dennis Zink(Universität Stuttgart)

May 21, 2020CAD-CAM

CAD-CAM(Universität Stuttgart)

May 21, 2020Institute of Aircraft Design

Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC

May 19, 2020 - B04: Hybrid discrete-continuum models for fractured porous media: model choice and random field/network generation

Reuschen, Sebastian; Xu, Teng; Nowak, Wolfgang, 2020, "Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC", https://doi.org/10.18419/DARUS-741, DaRUS, V1

This dataset contains the code and all relevant data and of the paper "Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC" by Sebastian Reuschen, Teng Xu and Wolfgang Nowak. Always cite the paper together with this dataset because this dataset is not self-explanatory. The code.tar.gz file conta...

code.tar.gz

May 19, 2020 - Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC

Gzip Archive - 143.7 KB -

data.tar.gz

May 19, 2020 - Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC

Gzip Archive - 580.8 MB -

Glycoside Hydrolase 19 Engineering Database(Universität Stuttgart)

May 18, 2020Bioinformatics

Supporting information and original files for bioinformatic investigations using the Glycoside Hydrolase 19 Engineering Database (https://gh19ed.biocatnet.de/)

SFB-TRR 161 A02 "Quantifying Visual Computing Systems"(Universität Stuttgart)

May 14, 2020SFB/Transregio 161 "Quantitative Methods for Visual Computing"

The long-term goal of this project is to quantify visual computing systems, i.e.to assess, model and ultimately predict important characteristics that have a substantial impact on user experience.

SFB-TRR 161 INF "Collaboration Infrastructure"(Universität Stuttgart, Universität Konstanz)

May 14, 2020SFB/Transregio 161 "Quantitative Methods for Visual Computing"

Project INF supports the other projects of SFB/Transregio 161 by providing a central approach to data management and an infrastructure for virtual meetings in a large, high-resolution display scenario.

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