Text representation through multimodal variational autoencoder for one-class learning (2023)
- Authors:
- USP affiliated authors: MARCACINI, RICARDO MARCONDES - ICMC ; GÔLO, MARCOS PAULO SILVA - ICMC
- Unidade: ICMC
- DOI: 10.5753/ctd.2023.229471
- Subjects: APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE TEXTO
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2023
- Source:
- Conference titles: Congresso da Sociedade Brasileira de Computação - CSBC
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
GÔLO, Marcos Paulo Silva e MARCACINI, Ricardo Marcondes. Text representation through multimodal variational autoencoder for one-class learning. 2023, Anais.. Porto Alegre: SBC, 2023. Disponível em: https://doi.org/10.5753/ctd.2023.229471. Acesso em: 24 dez. 2025. -
APA
Gôlo, M. P. S., & Marcacini, R. M. (2023). Text representation through multimodal variational autoencoder for one-class learning. In Anais. Porto Alegre: SBC. doi:10.5753/ctd.2023.229471 -
NLM
Gôlo MPS, Marcacini RM. Text representation through multimodal variational autoencoder for one-class learning [Internet]. Anais. 2023 ;[citado 2025 dez. 24 ] Available from: https://doi.org/10.5753/ctd.2023.229471 -
Vancouver
Gôlo MPS, Marcacini RM. Text representation through multimodal variational autoencoder for one-class learning [Internet]. Anais. 2023 ;[citado 2025 dez. 24 ] Available from: https://doi.org/10.5753/ctd.2023.229471 - One-class edge classification through heterogeneous hypergraph for causal discovery
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Informações sobre o DOI: 10.5753/ctd.2023.229471 (Fonte: oaDOI API)
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