1 to 10 of 13 Results
Feb 15, 2021 -
2d microstructure data
Hierarchical Data Format - 967.9 MB -
MD5: 8d93bd9af6585b0f63257c571920752c
hdf5 file containing all the data |
Feb 15, 2021 -
2d microstructure data
Python Source Code - 2.3 KB -
MD5: 8088ddd98656e04611bdf589220baf99
code to recompute/reproduce the data used for the regression problem |
Feb 15, 2021 -
2d microstructure data
Python Source Code - 1.9 KB -
MD5: be74203ddeb47af439f3cbc33594ac92
an example on how to access data stored in the hdf5 file |
Feb 15, 2021 -
2d microstructure data
Python Source Code - 3.8 KB -
MD5: 24355f5d0f71131cf836137a375fce75
dependency file for 'compute_regression_data.py' |
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" |
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" |
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" |
Jul 21, 2020 -
Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System
MS Excel Spreadsheet - 18.5 KB -
MD5: ed241c309250b1d17eb682b750fa1244
ANN parameters for the regularization method "MSE" |
Jul 21, 2020 -
Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System
Markdown Text - 3.0 KB -
MD5: 3aa442599a974dcf6b70ad2c45da506c
README file explaining how the data is formatted |
Jul 21, 2020 -
Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System
MATLAB Data - 493.4 MB -
MD5: 4368b82d61d591e5e7b76228741d13ae
This .mat file contains unprocessed input-output data pairs needed to train, validate, and test the ANN. |