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...

Descripción completa

Detalles Bibliográficos
Autores principales: Hatakeyama-Sato, Kan, Oyaizu, Kenichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
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

Internet

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

Ejemplares similares