Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic.

Quilodrán-Casas, César; Silva, Vinicius L S; Arcucci, Rossella; Heaney, Claire E; Guo, YiKe; Pain, Christopher C

Quilodrán-Casas, César; Silva, Vinicius L S; Arcucci, Rossella; Heaney, Claire E; Guo, YiKe; Pain, Christopher C.

Afiliação

Quilodrán-Casas C; Data Science Institute, Department of Computing, Imperial College London, UK.
Silva VLS; Department of Earth Science & Engineering, Imperial College London, UK.
Arcucci R; Department of Earth Science & Engineering, Imperial College London, UK.
Heaney CE; Data Science Institute, Department of Computing, Imperial College London, UK.
Guo Y; Department of Earth Science & Engineering, Imperial College London, UK.
Pain CC; Department of Earth Science & Engineering, Imperial College London, UK.

Neurocomputing (Amst) ; 470: 11-28, 2022 Jan 22.

Article em En | MEDLINE | ID: mdl-34703079

Palavras-chave

Deep learning; Digital twins; Generative adversarial networks; Long short-term memory networks; Reduced order models

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Neurocomputing (Amst) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido

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