Hands-on Deep Learning for Materials

This tool introduces users to deep learning techniques such as convolutional neural networks and variational auto encoders from a materials standpoint

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Version 1.3 - published on 20 Oct 2020

Open source: license | download

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Usage

World usage

Location of all "Hands-on Deep Learning for Materials" Users Since Its Posting

Cumulative Simulation Users

171

4 7 9 13 129 136 144 148 149 154 160 168 171

Users By Organization Type
Type Users
Unidentified 149 (87.13%)
Educational - University 19 (11.11%)
National Lab 3 (1.75%)
Users by Country of Residence
Country Users
us UNITED STATES 15 (71.43%)
in INDIA 2 (9.52%)
pk PAKISTAN 1 (4.76%)
de GERMANY 1 (4.76%)
tn TUNISIA 1 (4.76%)
hr CROATIA 1 (4.76%)

Simulation Runs

563

16 26 30 40 352 396 428 473 479 497 517 543 563
Overview
Average Total
Wall Clock Time 4 hours 52.96 days
CPU time 2.32 minutes 12.31 hours
Interaction Time 3.6 hours 47.76 days