Published November 9, 2022
| Version v1
Dataset
Open
Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data
- 1. Nano-Science Center and Department of Chemistry, University of Copenhagen, Denmark
- 2. School of Engineering and Materials Science, Queen Mary University of London, England
- 3. ISIS Neutron and Muon Source, Rutherford Appleton Laboratory, England
- 4. Scientific Computing Department, Rutherford Appleton Laboratory, England
Description
Files uploaded here are related to the paper titled "Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data". Here we investigate how generative adversarial networks can be used to match simulated- and experimental INS data.
Files
Files
(29.8 GB)
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md5:99a5b9d159b29f3598a04689379f8b67
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3.4 GB | Download |
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md5:f637780135e612af55d2fa062910e7e0
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md5:a4153f24b40e48f488a43f77f8ff90a6
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md5:233ed53987bba231aaf57b174bef97db
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md5:36d1edc84ab9b408a0c16a0e08dfefa5
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13.6 GB | Download |
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md5:7357402d9c314e8fe722c3909231141c
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4.4 GB | Download |
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md5:9a2969fa9089c0b89c3ad439db3ac727
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4.6 MB | Download |
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md5:74e4945e6642a23a6181cbbfe14eed37
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4.6 MB | Download |