SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning (2022)
- Authors:
- Autor USP: SILVA, JUAREZ LOPES FERREIRA DA - IQSC
- Unidade: IQSC
- DOI: 10.1021/acs.jcim.2c00521
- Subjects: MODELAGEM MOLECULAR; MOLÉCULA; QUÍMICA TEÓRICA
- Keywords: Electron correlation; Layers; Molecular properties
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Washington
- Date published: 2022
- Source:
- Título: Journal of Chemical Information and Modeling
- ISSN: 1549-960X
- Volume/Número/Paginação/Ano: v. 62, n.17, p. 3948–3960, 2022
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
PINHEIRO, Gabriel A. e SILVA, Juarez Lopes Ferreira da e QUILES, Marcos Gonçalves. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning. Journal of Chemical Information and Modeling, v. 62, n. 17, p. 3948–3960, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00521. Acesso em: 22 fev. 2026. -
APA
Pinheiro, G. A., Silva, J. L. F. da, & Quiles, M. G. (2022). SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning. Journal of Chemical Information and Modeling, 62( 17), 3948–3960. doi:10.1021/acs.jcim.2c00521 -
NLM
Pinheiro GA, Silva JLF da, Quiles MG. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 17): 3948–3960.[citado 2026 fev. 22 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521 -
Vancouver
Pinheiro GA, Silva JLF da, Quiles MG. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 17): 3948–3960.[citado 2026 fev. 22 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521 - Hybrid density functional study of small Rhn (n = 2−15) clusters
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Informações sobre o DOI: 10.1021/acs.jcim.2c00521 (Fonte: oaDOI API)
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