Journal article
Synthetic data enable experiments in atomistic machine learning
- Abstract:
-
En las últimas décadas, se ha producido un crecimiento exponencial en la generación, recopilación y almacenamiento de datos impulsado por el avance de la tecnología y la digitalización en diversos ámbitos. La invención de dispositivos móviles inteligentes, el avance de la instrumentación electrónica, el desarrollo de la tecnología IoT, todo ello sumado a la evolución de la capacidad de almacenamiento y de procesamiento computacional, han sido algunos factores destacados en el crecimiento vert...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1039/d2dd00137c
- Publication website:
- https://repositorio.unican.es/xmlui/bitstream/10902/29572/1/446983.pdf
Authors
+ UK Research and Innovation
More from this funder
- Funder identifier:
- 10.13039/100014013
- Grant:
- EP/X016188/1
+ John Fell Fund, University of Oxford
More from this funder
- Funder identifier:
- 10.13039/501100004789
- Grant:
- Support from the John Fell OUP Research Fund
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- 10.13039/501100000266
- Grant:
- EP/T517811/1
- Publisher:
- Royal Society of Chemistry
- Journal:
- Digital Discovery More from this journal
- Volume:
- 2
- Issue:
- 3
- Pages:
- 651-662
- Publication date:
- 2023-06-12
- DOI:
- EISSN:
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2635-098X
- ISSN:
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2635-098X
- Language:
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Spanish
- Keywords:
- Pubs id:
-
1518963
- Local pid:
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pubs:1518963
- Source identifiers:
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W4328023721
- Deposit date:
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2026-05-12
- ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.
Terms of use
- Copyright date:
- 2023
- Licence:
- CC Attribution (CC BY)
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