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NoiseMol: A noise-robusted data augmentation via perturbing noise for molecular property prediction.
Jiang, Jing; Zhang, Ruisheng; Yuan, Yongna; Li, Tongfeng; Li, Gaili; Zhao, Zhili; Yu, Zhixuan.
Afiliação
  • Jiang J; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China; Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education, Northwest Minzu University, Lanzhou, Gansu, China. Electronic address: jiangj2019@lzu.edu.cn.
  • Zhang R; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China. Electronic address: zhangrs@lzu.edu.cn.
  • Yuan Y; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China. Electronic address: yuanyn@lzu.edu.cn.
  • Li T; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China; Computer College, Qinghai Normal University, Xining, Qinghai, China. Electronic address: litf19@lzu.edu.cn.
  • Li G; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China. Electronic address: ligl2021@lzu.edu.cn.
  • Zhao Z; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China. Electronic address: zhaozhl@lzu.edu.cn.
  • Yu Z; School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu, China. Electronic address: yuzhx@lzu.edu.cn.
J Mol Graph Model ; 121: 108454, 2023 06.
Article em En | MEDLINE | ID: mdl-36963306
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Mol Graph Model Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Mol Graph Model Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2023 Tipo de documento: Article