Prediction of Atomic Stress Fields using Cycle-Consistent Adversarial Neural Networks based on Unpaired and Unmatched Sparse Datasets

Prediction of Atomic Stress Fields using Cycle-Consistent Adversarial Neural Networks based on Unpaired and Unmatched Sparse Datasets

<jats:p>Deep learning holds great promise for applications in materials science, including the discovery of physical laws and materials design.</jats:p>

Bibliografiska uppgifter
Huvudupphovsman: Buehler, Markus J
Övriga upphovsmän: Massachusetts Institute of Technology. Laboratory for Atomistic and Molecular Mechanics
Materialtyp: Artikel
Språk:English
Publicerad: Royal Society of Chemistry (RSC) 2022
Länkar:https://hdl.handle.net/1721.1/146552

Internet

https://hdl.handle.net/1721.1/146552

Liknande verk