Wu, Ling
Noels, Ludovic
2021-11-08
<p>Data related to<br>
===========<br>
title = "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step.",<br>
journal = "Computer Methods in Applied Mechanics and Engineering",<br>
volume ="390",<br>
year = "2022",<br>
doi = "https://doi.org/<a href="http://dx.doi.org/10.1016/j.cma.2021.114476">10.1016/j.cma.2021.114476</a> ",<br>
pages = "114476 ",<br>
author = "Wu, Ling and Noels, Ludovic"</p>
<p>We would be grateful if you could cite the paper in the case in which you are using the data</p>
<p> </p>
<p>The files replace version 1 whose zip was corrupted.</p>
<p> </p>
https://doi.org/10.5281/zenodo.5668390
oai:zenodo.org:5668390
ang
Zenodo
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.5653232
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Computer Methods in Applied Mechanics and Engineering, 390, 114476, (2021-11-08)
Recurrent neural networks
Multi-scale
Dimensionality Reduction
Localization step
History dependence
High dimensionality
Data of "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step."
info:eu-repo/semantics/other