Some of the data underlying the publication "Fighting the curse of dimensionality: A machine learning approach to finding global optima"
DOI:10.4121/17111648.v1
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DOI: 10.4121/17111648
DOI: 10.4121/17111648
Datacite citation style:
Julian Schumann (2021): Some of the data underlying the publication "Fighting the curse of dimensionality: A machine learning approach to finding global optima". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/17111648.v1
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Dataset
The data assembled here should allow the reproduction of the Figures 4 and 6 from the mentioned paper. The corresponding code can be found at https://github.com/julianschumann/ae-opt.
History
- 2021-12-03 first online, published, posted
Publisher
4TU.ResearchDataFormat
.h5 .npyOrganizations
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3mE)DATA
Files (2)
- 100,151,460 bytesMD5:
8fb59bbe5abe4db98ebb65ed936749be
Sample_data_4.zip - 254,026,315 bytesMD5:
bbf5589067cd62dddacb466fa34ba434
Sample_data_6.zip -
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