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Keyword Term: Machine Learning

11 to 20 of 20 Results

Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems 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...
Replication Code for: Meta-Uncertainty in Bayesian Model Comparison May 25, 2023 - Data and Code for: Meta-Uncertainty in Bayesian Model Comparison 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)....
Image enhancement code: time-resolved tomograms of EICP application using 3D U-net 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...
Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials Jan 11, 2023 - Materials Design Jung, Jong Hyun; Srinivasan, Prashanth; Forslund, Axel; Grabowski, Blazej, 2023, "Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials", https://doi.org/10.18419/darus-3239, DaRUS, V1 Data for the publication High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials, npj Comput. Mater., DOI: 10.1038/s41524-022-00956-8 (2023) This data set contains - the training sets (VASP files), - the low mom...
Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network Nov 2, 2022 - PN 5-6 Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, Wolfgang, 2022, "Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network", https://doi.org/10.18419/darus-3249, DaRUS, V1 This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir isotherms. This dataset is used to train, validate, and test all the deep learning models that are used in t...
NMTVis - Extended Neural Machine Translation Visualization System Jan 26, 2022 - PN 6-4 Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2022, "NMTVis - Extended Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-2124, 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...
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...
NMTVis - Trained Models for our Visual Analytics System May 26, 2021 - PN 6-4 Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Trained Models for our Visual Analytics System", https://doi.org/10.18419/darus-1850, DaRUS, V1 Trained models and vocabulary files for the use in our visual analytics system NMTVis. There are models for German to English and vice versa available for an LSTM-based and the Transformer architecture.
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...

Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems

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...

Replication Code for: Meta-Uncertainty in Bayesian Model Comparison

May 25, 2023 - Data and Code for: Meta-Uncertainty in Bayesian Model Comparison

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)....

Image enhancement code: time-resolved tomograms of EICP application using 3D U-net

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...

Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials

Jan 11, 2023 - Materials Design

Jung, Jong Hyun; Srinivasan, Prashanth; Forslund, Axel; Grabowski, Blazej, 2023, "Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials", https://doi.org/10.18419/darus-3239, DaRUS, V1

Data for the publication High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials, npj Comput. Mater., DOI: 10.1038/s41524-022-00956-8 (2023) This data set contains - the training sets (VASP files), - the low mom...

Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network

Nov 2, 2022 - PN 5-6

Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, Wolfgang, 2022, "Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network", https://doi.org/10.18419/darus-3249, DaRUS, V1

This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir isotherms. This dataset is used to train, validate, and test all the deep learning models that are used in t...

NMTVis - Extended Neural Machine Translation Visualization System

Jan 26, 2022 - PN 6-4

Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2022, "NMTVis - Extended Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-2124, 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...

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...

NMTVis - Trained Models for our Visual Analytics System

May 26, 2021 - PN 6-4

Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Trained Models for our Visual Analytics System", https://doi.org/10.18419/darus-1850, DaRUS, V1

Trained models and vocabulary files for the use in our visual analytics system NMTVis. There are models for German to English and vice versa available for an LSTM-based and the Transformer architecture.

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

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