Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling
Abstract The crystal diffusion variational autoencoder (CDVAE) is a machine learning model that leverages score matching to generate realistic crystal structures that preserve crystal symmetry. In this study, we leverage novel diffusion probabilistic (DP) models to denoise atomic coordinates rather...
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| Principais autores: | , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Nature Portfolio
2024-01-01
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| Series: | Scientific Reports |
| Acceso en liña: | https://doi.org/10.1038/s41598-024-51400-4 |
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