<div class="csl-bib-body">
<div class="csl-entry">Favoni, M., Ipp, A., & Müller, D. (2022). Applications of Lattice Gauge Equivariant Neural Networks. In A. Rothkopf (Ed.), <i>XVth Quark Confinement and the Hadron Spectrum Conference (ConfXV)</i>. EPJ Web of Conferences. https://doi.org/10.1051/epjconf/202227409001</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/142237
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dc.description.abstract
The introduction of relevant physical information into neural network architectures has become a widely used and successful strategy for improving their performance. In lattice gauge theories, such information can be identified with gauge symmetries, which are incorporated into the network layers of our recently proposed Lattice Gauge Equivariant Convolutional Neural Networks (L-CNNs). L-CNNs can generalize better to differently sized lattices than traditional neural networks and are by construction equivariant under lattice gauge transformations. In these proceedings, we present our progress on possible applications of L-CNNs to Wilson flow or continuous normalizing flow. Our methods are based on neural ordinary differential equations which allow us to modify link configurations in a gauge equivariant manner. For simplicity, we focus on simple toy models to test these ideas in practice.
en
dc.language.iso
en
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dc.subject
Neural Networks
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dc.subject
gauge symmetry
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dc.subject
Gradient flow
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dc.title
Applications of Lattice Gauge Equivariant Neural Networks
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.editoraffiliation
University of Stavanger, Norway
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dcterms.dateSubmitted
2022-12-01
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
XVth Quark Confinement and the Hadron Spectrum Conference (ConfXV)
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tuw.container.volume
274
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tuw.relation.publisher
EPJ Web of Conferences
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tuw.researchTopic.id
C5
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tuw.researchTopic.id
C6
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tuw.researchTopic.name
Computer Science Foundations
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tuw.researchTopic.name
Modeling and Simulation
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tuw.researchTopic.value
20
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tuw.researchTopic.value
80
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tuw.publication.orgunit
E136 - Institut für Theoretische Physik
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tuw.publisher.doi
10.1051/epjconf/202227409001
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dc.description.numberOfPages
8
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tuw.author.orcid
0000-0001-9511-3523
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tuw.author.orcid
0000-0002-8163-7614
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tuw.editor.orcid
0000-0002-5526-0809
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tuw.event.name
XVth Quark Confinement and the Hadron Spectrum Conference (ConfXV) 2022