Learning to sense from events via semantic variational autoencoder (2021)
- Authors:
- USP affiliated authors: MARCACINI, RICARDO MARCONDES - ICMC ; GÔLO, MARCOS PAULO SILVA - ICMC
- Unidade: ICMC
- DOI: 10.1371/journal.pone.0260701
- Subjects: RECONHECIMENTO DE TEXTO; APRENDIZADO COMPUTACIONAL; PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS)
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: San Francisco
- Date published: 2021
- Source:
- Status:
- Artigo publicado em periódico de acesso aberto (Gold Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
GÔLO, Marcos Paulo Silva e ROSSI, Rafael Geraldeli e MARCACINI, Ricardo Marcondes. Learning to sense from events via semantic variational autoencoder. PLoS ONE, v. 16, n. 2, p. 1-20, 2021Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0260701. Acesso em: 30 mar. 2026. -
APA
Gôlo, M. P. S., Rossi, R. G., & Marcacini, R. M. (2021). Learning to sense from events via semantic variational autoencoder. PLoS ONE, 16( 2), 1-20. doi:10.1371/journal.pone.0260701 -
NLM
Gôlo MPS, Rossi RG, Marcacini RM. Learning to sense from events via semantic variational autoencoder [Internet]. PLoS ONE. 2021 ; 16( 2): 1-20.[citado 2026 mar. 30 ] Available from: https://doi.org/10.1371/journal.pone.0260701 -
Vancouver
Gôlo MPS, Rossi RG, Marcacini RM. Learning to sense from events via semantic variational autoencoder [Internet]. PLoS ONE. 2021 ; 16( 2): 1-20.[citado 2026 mar. 30 ] Available from: https://doi.org/10.1371/journal.pone.0260701 - Improving natural product knowledge extraction from academic literature with enhanced PDF text extraction and large language models
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