Recovering network topology and dynamics from sequences: a machine learning approach (2024)
Source: Physica A : statistical mechanics and its applications. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, HEURÍSTICA
ABNT
GUERREIRO, Lucas e SILVA, Filipi Nascimento e AMANCIO, Diego Raphael. Recovering network topology and dynamics from sequences: a machine learning approach. Physica A : statistical mechanics and its applications, v. 638, p. 1-13, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2024.129618. Acesso em: 28 abr. 2024.APA
Guerreiro, L., Silva, F. N., & Amancio, D. R. (2024). Recovering network topology and dynamics from sequences: a machine learning approach. Physica A : statistical mechanics and its applications, 638, 1-13. doi:10.1016/j.physa.2024.129618NLM
Guerreiro L, Silva FN, Amancio DR. Recovering network topology and dynamics from sequences: a machine learning approach [Internet]. Physica A : statistical mechanics and its applications. 2024 ; 638 1-13.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1016/j.physa.2024.129618Vancouver
Guerreiro L, Silva FN, Amancio DR. Recovering network topology and dynamics from sequences: a machine learning approach [Internet]. Physica A : statistical mechanics and its applications. 2024 ; 638 1-13.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1016/j.physa.2024.129618