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...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-05-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-13007-5 |