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Generative Models for Extrapolation Prediction in Materials Informatics
[Image: see text] We report a deep generative model for regression tasks in materials informatics. The model is introduced as a component of a data imputer and predicts more than 20 diverse experimental properties of organic molecules. The imputer is designed to predict material properties by “imagi...
Autores principales: | Hatakeyama-Sato, Kan, Oyaizu, Kenichi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190893/ https://www.ncbi.nlm.nih.gov/pubmed/34124480 http://dx.doi.org/10.1021/acsomega.1c01716 |
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