Polymer informatics with multi-task learning

Modern data-driven tools are transforming application-specific polymer development cycles. Surrogate models that can be trained to predict properties of polymers are becoming commonplace. Nevertheless, these models do not utilize the full breadth of the knowledge available in datasets, which are oft...

Descripción completa

Detalles Bibliográficos
Autores principales: Kuenneth, Christopher, Rajan, Arunkumar Chitteth, Tran, Huan, Chen, Lihua, Kim, Chiho, Ramprasad, Rampi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085610/
https://www.ncbi.nlm.nih.gov/pubmed/33982028
http://dx.doi.org/10.1016/j.patter.2021.100238

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085610/
https://www.ncbi.nlm.nih.gov/pubmed/33982028
http://dx.doi.org/10.1016/j.patter.2021.100238

Ejemplares similares