Optimization of physical quantities in the autoencoder latent space

Abstract We propose a strategy for optimizing physical quantities based on exploring in the latent space of a variational autoencoder (VAE). We train a VAE model using various spin configurations formed on a two-dimensional chiral magnetic system. Three optimization algorithms are used to explore th...

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Bibliographic Details
Main Authors: S. M. Park, H. G. Yoon, D. B. Lee, J. W. Choi, H. Y. Kwon, C. Won
Format: Article
Language:English
Published: Nature Portfolio 2022-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-13007-5