Neural Network Renormalization Group
We present a variational renormalization group (RG) approach based on a reversible generative model with hierarchical architecture. The model performs hierarchical change-of-variables transformations from the physical space to a latent space with reduced mutual information. Conversely, the neural ne...
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Published in | Physical review letters Vol. 121; no. 26; p. 260601 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
United States
28.12.2018
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Online Access | Get more information |
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