Views provided by UsageCountsUsing generative adversarial networks to match experimental and simulated inelastic neutron scattering data
Anker, Andy S.; Butler, Keith T.; Le, Manh D.; Perring, Toby G.; Thiyagalingam, Jeyan;
Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data
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.
- University of Copenhagen Denmark
- Queen Mary University of London United Kingdom
- Rutherford Appleton Laboratory United Kingdom
- Science and Technology Facilities Council United Kingdom
Machine Learning, Inelastic Neutron Scattering, Generative Adversarial Networks, Experimental Data, Spectroscopy, Materials Chemistry, Artificial Intelligence, Materials Discovery, Materials Informatics
Machine Learning, Inelastic Neutron Scattering, Generative Adversarial Networks, Experimental Data, Spectroscopy, Materials Chemistry, Artificial Intelligence, Materials Discovery, Materials Informatics
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average views 1 - 1views
selected citations
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP!influenceInfluence provided by BIP!
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Influence provided by BIP!impulseImpulse provided by BIP!
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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