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
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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: 08 nov. 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.2024.0435NLM
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 nov. 08 ] Available from: https://doi.org/10.1098/rspa.2024.0435Vancouver
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 nov. 08 ] Available from: https://doi.org/10.1098/rspa.2024.0435
