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Filtros : "Humboldt University" Limpar

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  • Artigo de periodico

    A machine learning approach to predicting dynamical observables from network structure (2024)

    Rodrigues, Francisco Aparecido ; Peron, Thomas ; Connaughton, Colm ; Kurths, Jürgen ; Moreno, Yamir

    Source: Proceedings of the Royal Society A. Unidade: ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, SISTEMAS DINÂMICOS

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      RODRIGUES, Francisco Aparecido et al. A machine learning approach to predicting dynamical observables from network structure. Proceedings of the Royal Society A, v. 481, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1098/rspa.2024.0435. Acesso em: 02 dez. 2025.

    • APA

      Rodrigues, F. A., Peron, T., Connaughton, C., Kurths, J., & Moreno, Y. (2024). A machine learning approach to predicting dynamical observables from network structure. Proceedings of the Royal Society A, 481, 1-12. doi:10.1098/rspa.2024.0435

    • NLM

      Rodrigues FA, Peron T, Connaughton C, Kurths J, Moreno Y. A machine learning approach to predicting dynamical observables from network structure [Internet]. Proceedings of the Royal Society A. 2024 ; 481 1-12.[citado 2025 dez. 02 ] Available from: https://doi.org/10.1098/rspa.2024.0435

    • Vancouver

      Rodrigues FA, Peron T, Connaughton C, Kurths J, Moreno Y. A machine learning approach to predicting dynamical observables from network structure [Internet]. Proceedings of the Royal Society A. 2024 ; 481 1-12.[citado 2025 dez. 02 ] Available from: https://doi.org/10.1098/rspa.2024.0435

  • Artigo de periodico

    Performance measures after perturbations in the presence of inertia (2021)

    Ye, Jiachen; Peron, Thomas ; Lin, Wei; Kurths, Jürgen; Ji, Peng

    Source: Communications in Nonlinear Science and Numerical Simulation. Unidade: ICMC

    Subjects: REDES COMPLEXAS, SISTEMAS DINÂMICOS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      YE, Jiachen et al. Performance measures after perturbations in the presence of inertia. Communications in Nonlinear Science and Numerical Simulation, v. 97, p. 1-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.cnsns.2021.105727. Acesso em: 02 dez. 2025.

    • APA

      Ye, J., Peron, T., Lin, W., Kurths, J., & Ji, P. (2021). Performance measures after perturbations in the presence of inertia. Communications in Nonlinear Science and Numerical Simulation, 97, 1-10. doi:10.1016/j.cnsns.2021.105727

    • NLM

      Ye J, Peron T, Lin W, Kurths J, Ji P. Performance measures after perturbations in the presence of inertia [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2021 ; 97 1-10.[citado 2025 dez. 02 ] Available from: https://doi.org/10.1016/j.cnsns.2021.105727

    • Vancouver

      Ye J, Peron T, Lin W, Kurths J, Ji P. Performance measures after perturbations in the presence of inertia [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2021 ; 97 1-10.[citado 2025 dez. 02 ] Available from: https://doi.org/10.1016/j.cnsns.2021.105727
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