Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems
| Identifier | |
|---|---|
| DOI | https://doi.org/10.24435/materialscloud:2018.0009/v1 |
| Related Identifier | https://doi.org/10.1103/PhysRevLett.120.036002 |
| Related Identifier | https://archive.materialscloud.org/communities/mcarchive |
| Related Identifier | https://doi.org/10.24435/materialscloud:nv-dg |
| Metadata Access | https://archive.materialscloud.org/oai2d?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:43 |
| Provenance | |
|---|---|
| Creator | Grisafi, Andrea; Wilkins, David M.; Csányi, Gabor; Ceriotti, Michele |
| Publisher | Materials Cloud |
| Contributor | Wilkins, David M. |
| Publication Year | 2018 |
| Rights | info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/legalcode |
| OpenAccess | true |
| Contact | archive(at)materialscloud.org |
| Representation | |
|---|---|
| Language | English |
| Resource Type | info:eu-repo/semantics/other |
| Format | text/plain; chemical/x-xyz; text/markdown |
| Discipline | Materials Science and Engineering |
