Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ryan J. Murdock"'
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
Abstract In this paper, we demonstrate an application of the Transformer self-attention mechanism in the context of materials science. Our network, the Compositionally Restricted Attention-Based network (CrabNet), explores the area of structure-agnos
Externí odkaz:
https://doaj.org/article/84ef20134dd54902b0ccba0b112204ea
Publikováno v:
Integrating Materials and Manufacturing Innovation. 9:221-227
New featurization schemes for describing materials as composition vectors in order to predict their properties using machine learning are common in the field of Materials Informatics. However, little is known about the comparative efficacy of these m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97d1af3905412089e73d207f7c8a574d
https://doi.org/10.1007/s40192-020-00179-z
https://doi.org/10.1007/s40192-020-00179-z
Autor:
Ryan J. Murdock, Kristin A. Persson, Jakoah Brgoch, Steven K. Kauwe, Anton O. Oliynyk, Aleksander Gurlo, Taylor D. Sparks, Anthony Yu-Tung Wang
Publikováno v:
Chemistry of Materials. 32:4954-4965
This Methods/Protocols article is intended for materials scientists interested in performing machine learning-centered research. We cover broad guidelines and best practices regarding the obtaining...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b670d8509d7e68ae1f0e4f7e1b519dc8
https://doi.org/10.1021/acs.chemmater.0c01907
https://doi.org/10.1021/acs.chemmater.0c01907
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
In this paper, we demonstrate an application of the Transformer self-attention mechanism in the context of materials science. Our network, the Compositionally Restricted Attention-Based network (), explores the area of structure-agnostic materials pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::663a51a406f252dc38bd64c8f1309656
https://doi.org/10.1038/s41524-021-00545-1
https://doi.org/10.1038/s41524-021-00545-1
Autor:
Jakoah Brgoch, Kristin A. Persson, Anthony Yu-Tung Wang, Steven K. Kauwe, Ryan J. Murdock, Aleksander Gurlo, Taylor D. Sparks, Anton O. Oliynyk
This Editorial is intended for materials scientists interested in performing machine learning-centered research.We cover broad guidelines and best practices regarding the obtaining and treatment of data, feature engineering, model training, validatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1152c8e22b54ade2b091e07f81fb93c4
https://doi.org/10.26434/chemrxiv.12249752.v1
https://doi.org/10.26434/chemrxiv.12249752.v1
Publikováno v:
Journal of Vision. 21:2649
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e260d5916ffcc3acfa9438d6859d09d5
https://doi.org/10.1167/jov.21.9.2649
https://doi.org/10.1167/jov.21.9.2649