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A cautionary tale for machine learning generated configurations in presence of a conserved quantity

We investigate the performance of machine learning algorithms trained exclusively with configurations obtained from importance sampling Monte Carlo simulations of the two-dimensional Ising model with conserved magnetization. For supervised machine learning, we use convolutional neural networks and f...

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Detalles Bibliográficos
Autores principales: Azizi, Ahmadreza, Pleimling, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973807/
https://www.ncbi.nlm.nih.gov/pubmed/33737630
http://dx.doi.org/10.1038/s41598-021-85683-8

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