DaRUS

Metrics

1,190,826 Downloads

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Publication Year: 2021 Funding Information Identifier: EXC 2075 - 390740016

1 to 10 of 11 Results

Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B' Nov 25, 2021 - Molecular Simulation Markthaler, Daniel; Hansen, Niels, 2021, "Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'", https://doi.org/10.18419/darus-2104, DaRUS, V1 This dataset contains all relevant simulation input files (topologies, coordinates, simulation parameters), generated simulation output (final configurations, time series of collective variables) together with scripts used for set-up and analysis of the umbrella sampling and doub...
Code for relative permeabilities for two-phase flow between parallel plates with slip conditions Nov 24, 2021 - PN 1-6 Schulz, Sebastian; Bringedal, Carina; Ackermann, Sina, 2021, "Code for relative permeabilities for two-phase flow between parallel plates with slip conditions", https://doi.org/10.18419/darus-2241, DaRUS, V1 This MATLAB code calculates relative permeabilities of two fluids flowing between two parallel plates, depending on their viscosities, saturation and boundary conditions at the top and bottom plates. The underlying assumptions behind the derivation are shown in the pdf "overview_...
Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments Oct 15, 2021 - PN 6 Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/darus-2136, DaRUS, V1 Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab
Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity" Oct 5, 2021 - PN 6-6 Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1 We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details.
Visual Analytics System for Hidden States in Recurrent Neural Networks Sep 10, 2021 - PN 6-4 Munz, Tanja; Garcia, Rafael; Weiskopf, Daniel, 2021, "Visual Analytics System for Hidden States in Recurrent Neural Networks", https://doi.org/10.18419/darus-2052, DaRUS, V1 Source code of our visual analytics system for the interpretation of hidden states in recurrent neural networks. This project contains source code for preprocessing data and the visual analytics system. Additionally, we added precomputed data for immediate use in the visual analy...
Simulation input scripts for "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces" Aug 20, 2021 - Paper Nature Materials 2021 Schlaich, Alexander, 2021, "Simulation input scripts for "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces"", https://doi.org/10.18419/darus-2115, DaRUS, V1 This dataset includes the basic simulation scripts needed in order to reproduce the data shown in "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces". The folder structure corresponds to the ind...
Replication Data for: Load-Balancing for Scalable Simulations with Large Particle Numbers Jun 7, 2021 - Publications Hirschmann, Steffen, 2021, "Replication Data for: Load-Balancing for Scalable Simulations with Large Particle Numbers", https://doi.org/10.18419/darus-1851, DaRUS, V1, UNF:6:WXqt4IDAIDGnJB9tcwMhdg== [fileUNF] This dataset contains input data, scripts, etc. for replicating the numerical experiments in Steffen Hirschmann's dissertation. The data is prefixed with folders indicating the specific experiment as is the processing metadata. The experiments are: 00_periodicity_experiment: Expe...
NMTVis - Neural Machine Translation Visualization System May 26, 2021 - PN 6-4 Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-1849, DaRUS, V1 NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...
A Data Set for Research on Data-based Methods for an Omnidirectional Mobile Robot May 21, 2021 - PN 4-4 Eschmann, Hannes, 2021, "A Data Set for Research on Data-based Methods for an Omnidirectional Mobile Robot", https://doi.org/10.18419/darus-1845, DaRUS, V1 The intend of this data set is the cooperation within SimTech. It will be particularly interesting for data-based modeling and control which is a key area of the research of project network 4. We are proud to provide real-world data, which is essential for the benchmark of any da...
Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Mar 23, 2021 - PN 6-3 Holzmüller, David, 2021, "Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression", https://doi.org/10.18419/darus-1771, DaRUS, V1 This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally pro...

Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'

Nov 25, 2021 - Molecular Simulation

Markthaler, Daniel; Hansen, Niels, 2021, "Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'", https://doi.org/10.18419/darus-2104, DaRUS, V1

This dataset contains all relevant simulation input files (topologies, coordinates, simulation parameters), generated simulation output (final configurations, time series of collective variables) together with scripts used for set-up and analysis of the umbrella sampling and doub...

Code for relative permeabilities for two-phase flow between parallel plates with slip conditions

Nov 24, 2021 - PN 1-6

Schulz, Sebastian; Bringedal, Carina; Ackermann, Sina, 2021, "Code for relative permeabilities for two-phase flow between parallel plates with slip conditions", https://doi.org/10.18419/darus-2241, DaRUS, V1

This MATLAB code calculates relative permeabilities of two fluids flowing between two parallel plates, depending on their viscosities, saturation and boundary conditions at the top and bottom plates. The underlying assumptions behind the derivation are shown in the pdf "overview_...

Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments

Oct 15, 2021 - PN 6

Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/darus-2136, DaRUS, V1

Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab

Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"

Oct 5, 2021 - PN 6-6

Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1

We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details.

Visual Analytics System for Hidden States in Recurrent Neural Networks

Sep 10, 2021 - PN 6-4

Munz, Tanja; Garcia, Rafael; Weiskopf, Daniel, 2021, "Visual Analytics System for Hidden States in Recurrent Neural Networks", https://doi.org/10.18419/darus-2052, DaRUS, V1

Source code of our visual analytics system for the interpretation of hidden states in recurrent neural networks. This project contains source code for preprocessing data and the visual analytics system. Additionally, we added precomputed data for immediate use in the visual analy...

Simulation input scripts for "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces"

Aug 20, 2021 - Paper Nature Materials 2021

Schlaich, Alexander, 2021, "Simulation input scripts for "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces"", https://doi.org/10.18419/darus-2115, DaRUS, V1

This dataset includes the basic simulation scripts needed in order to reproduce the data shown in "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces". The folder structure corresponds to the ind...

Replication Data for: Load-Balancing for Scalable Simulations with Large Particle Numbers

Jun 7, 2021 - Publications

Hirschmann, Steffen, 2021, "Replication Data for: Load-Balancing for Scalable Simulations with Large Particle Numbers", https://doi.org/10.18419/darus-1851, DaRUS, V1, UNF:6:WXqt4IDAIDGnJB9tcwMhdg== [fileUNF]

This dataset contains input data, scripts, etc. for replicating the numerical experiments in Steffen Hirschmann's dissertation. The data is prefixed with folders indicating the specific experiment as is the processing metadata. The experiments are: 00_periodicity_experiment: Expe...

NMTVis - Neural Machine Translation Visualization System

May 26, 2021 - PN 6-4

Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-1849, DaRUS, V1

NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...

A Data Set for Research on Data-based Methods for an Omnidirectional Mobile Robot

May 21, 2021 - PN 4-4

Eschmann, Hannes, 2021, "A Data Set for Research on Data-based Methods for an Omnidirectional Mobile Robot", https://doi.org/10.18419/darus-1845, DaRUS, V1

The intend of this data set is the cooperation within SimTech. It will be particularly interesting for data-based modeling and control which is a key area of the research of project network 4. We are proud to provide real-world data, which is essential for the benchmark of any da...

Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Mar 23, 2021 - PN 6-3

Holzmüller, David, 2021, "Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression", https://doi.org/10.18419/darus-1771, DaRUS, V1

This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally pro...

Add Data

Share Dataverse

Link Dataverse

Reset Modifications