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Filtros : "Calderan, Felipe V" Limpar

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  • Parte de monografia/livro

    Guided clustering for selecting representatives samples in chemical databases (2023)

    Calderan, Felipe V ; Mendonça, João Paulo A. de ; Silva, Juarez Lopes Ferreira da ; Quiles, Marcos Gonçalves

    Source: Computational Science and Its Applications. ICCSA 2023. Lecture Notes in Computer Science. Unidade: IQSC

    Subjects: CIÊNCIA DA COMPUTAÇÃO, QUÍMICA, MATERIAIS

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    • ABNT

      CALDERAN, Felipe V et al. Guided clustering for selecting representatives samples in chemical databases. Computational Science and Its Applications. ICCSA 2023. Lecture Notes in Computer Science. Tradução . Cham: Instituto de Química de São Carlos, Universidade de São Paulo, 2023. . Disponível em: https://doi.org/10.1007/978-3-031-37126-4_10. Acesso em: 07 jun. 2024.

    • APA

      Calderan, F. V., Mendonça, J. P. A. de, Silva, J. L. F. da, & Quiles, M. G. (2023). Guided clustering for selecting representatives samples in chemical databases. In Computational Science and Its Applications. ICCSA 2023. Lecture Notes in Computer Science. Cham: Instituto de Química de São Carlos, Universidade de São Paulo. doi:10.1007/978-3-031-37126-4_10

    • NLM

      Calderan FV, Mendonça JPA de, Silva JLF da, Quiles MG. Guided clustering for selecting representatives samples in chemical databases [Internet]. In: Computational Science and Its Applications. ICCSA 2023. Lecture Notes in Computer Science. Cham: Instituto de Química de São Carlos, Universidade de São Paulo; 2023. [citado 2024 jun. 07 ] Available from: https://doi.org/10.1007/978-3-031-37126-4_10

    • Vancouver

      Calderan FV, Mendonça JPA de, Silva JLF da, Quiles MG. Guided clustering for selecting representatives samples in chemical databases [Internet]. In: Computational Science and Its Applications. ICCSA 2023. Lecture Notes in Computer Science. Cham: Instituto de Química de São Carlos, Universidade de São Paulo; 2023. [citado 2024 jun. 07 ] Available from: https://doi.org/10.1007/978-3-031-37126-4_10

  • Trabalho de evento

    The impact of low-cost molecular geometry optimization in property prediction via graph neural network (2022)

    Pinheiro, Gabriel A ; Calderan, Felipe V ; Silva, Juarez Lopes Ferreira da ; Quiles, Marcos Gonçalves

    Source: Book of Abstracts. Conference titles: IEEE International Conference on Machine Learning and Applications (ICMLA). Unidade: IQSC

    Subjects: ESTRUTURA MOLECULAR (QUÍMICA TEÓRICA), REDES NEURAIS, ALGORITMOS

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    • ABNT

      PINHEIRO, Gabriel A et al. The impact of low-cost molecular geometry optimization in property prediction via graph neural network. 2022, Anais.. Nassau: Instituto de Química de São Carlos, Universidade de São Paulo, 2022. p. 603-608. Disponível em: https://doi.org/10.1109/ICMLA55696.2022.00092. Acesso em: 07 jun. 2024.

    • APA

      Pinheiro, G. A., Calderan, F. V., Silva, J. L. F. da, & Quiles, M. G. (2022). The impact of low-cost molecular geometry optimization in property prediction via graph neural network. In Book of Abstracts (p. 603-608). Nassau: Instituto de Química de São Carlos, Universidade de São Paulo. doi:10.1109/ICMLA55696.2022.00092

    • NLM

      Pinheiro GA, Calderan FV, Silva JLF da, Quiles MG. The impact of low-cost molecular geometry optimization in property prediction via graph neural network [Internet]. Book of Abstracts. 2022 ; 603-608.[citado 2024 jun. 07 ] Available from: https://doi.org/10.1109/ICMLA55696.2022.00092

    • Vancouver

      Pinheiro GA, Calderan FV, Silva JLF da, Quiles MG. The impact of low-cost molecular geometry optimization in property prediction via graph neural network [Internet]. Book of Abstracts. 2022 ; 603-608.[citado 2024 jun. 07 ] Available from: https://doi.org/10.1109/ICMLA55696.2022.00092
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