Studies of Shape Memory Graphene Nanostructures via Integration of Physics-based Modelling and Machine Learning - Revision history of "Leon Melnik 2021a" - Scipedia

Presentations and Plenary videos to 9th edition of the International Conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED PROBLEMS 2021)

C. León, R. Melnik

Diff selection: Mark the radio boxes of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.

Back to Top

GET PDF

Document information

Published on 11/07/21
Submitted on 11/07/21

Volume IS25 - Physics Informed Machine Learning For Scientific Computing, 2021
DOI: 10.23967/coupled.2021.053
Licence: CC BY-NC-SA license

Share this document

Keywords

Combining physiscs-based and machine learning approaches • Complex systems • Graphene nanostructures with shape memory effects • Many-body tensor representation • DFT calculations • Advanced scientific problems

claim authorship

Are you one of the authors of this document?