Stuttgart Center for Simulation Science (SC SimTech)

EXC 2075 Project Networks

SIGDIUS

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21,121 to 21,130 of 21,172 Results

exampleData.zip Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games ZIP Archive - 101.2 MB - MD5: dd836aa0f27d6260f8b011143a6ae60d Example dataset that was recorded with two different eye trackers; it can be loaded into the analysis system
materials.zip Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games ZIP Archive - 1.0 MB - MD5: 78e6d3f046a965031bfc2f51055a11f4 Additional information about Go
README.md Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games Markdown Text - 6.3 KB - MD5: d3274de99af618853a65ef6a2704dd45 Information about the analysis system
release.zip Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games ZIP Archive - 29.5 MB - MD5: 2e358ba20bb0d45552fa4e6066220390 Executable files of the analysis system
sourceCode.zip Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games ZIP Archive - 29.5 MB - MD5: cf60c265a2cb8e048f2ca44d571ad19a Java source code of the analysis system
PN 6-4(Universität Stuttgart) Oct 27, 2020PN 6 SimTech Project PN 6-4 "Visual Analytics for Deep Learning"
Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System Jul 21, 2020 - PINN Dynamic System Praditia, Timothy, 2020, "Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/DARUS-634, DaRUS, V1 This dataset contains four .xlsx files containing trained values of the ANN weights and biases, along with the hyperparameter values at the end of the training (with noisy dataset). These four files correspond to four different regularization methods.
ANN_params_MSE_L2_PHY.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 19.1 KB - MD5: 9b88868eeef277937d0c729615e217de ANN parameters for the regularization method "MSE+L2+PHY"
ANN_params_MSE_L2.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 18.7 KB - MD5: 9a85fe1d359cb162a8c4bc183545ce46 ANN parameters for the regularization method "MSE+L2"
ANN_params_MSE_PHY.xlsx Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System MS Excel Spreadsheet - 19.0 KB - MD5: 1b13a37e8fb1bf8ee2630519982ae0e4 ANN parameters for the regularization method "MSE+PHY"

exampleData.zip

Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games

ZIP Archive - 101.2 MB -

Example dataset that was recorded with two different eye trackers; it can be loaded into the analysis system

materials.zip

Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games

ZIP Archive - 1.0 MB -

Additional information about Go

README.md

Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games

Markdown Text - 6.3 KB -

Information about the analysis system

release.zip

Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games

ZIP Archive - 29.5 MB -

Executable files of the analysis system

sourceCode.zip

Nov 2, 2020 - Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games

ZIP Archive - 29.5 MB -

Java source code of the analysis system

PN 6-4(Universität Stuttgart)

Oct 27, 2020PN 6

SimTech Project PN 6-4 "Visual Analytics for Deep Learning"

Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

Jul 21, 2020 - PINN Dynamic System

Praditia, Timothy, 2020, "Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/DARUS-634, DaRUS, V1

This dataset contains four .xlsx files containing trained values of the ANN weights and biases, along with the hyperparameter values at the end of the training (with noisy dataset). These four files correspond to four different regularization methods.

ANN_params_MSE_L2_PHY.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 19.1 KB -

ANN parameters for the regularization method "MSE+L2+PHY"

ANN_params_MSE_L2.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 18.7 KB -

ANN parameters for the regularization method "MSE+L2"

ANN_params_MSE_PHY.xlsx

Jul 21, 2020 - Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

MS Excel Spreadsheet - 19.0 KB -

ANN parameters for the regularization method "MSE+PHY"

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