Energy-weighted message passing: an infra-red and collinear safe graph neural network algorithm
Abstract Hadronic signals of new-physics origin at the Large Hadron Collider can remain hidden within the copiously produced hadronic jets. Unveiling such signatures require highly performant deep-learning algorithms. We construct a class of Graph Neural Networks (GNN) in the message-passing formali...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
SpringerOpen
2022-02-01
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| coleção: | Journal of High Energy Physics |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/JHEP02(2022)060 |
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