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  • Source: IEEE Transactions on Network Science and Engineering. Unidades: FFCLRP, ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, DESCOBERTA DE CONHECIMENTO, ALGORITMOS ÚTEIS E ESPECÍFICOS, REDES COMPLEXAS

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      VALEJO, Alan Demetrius Baria et al. Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks. IEEE Transactions on Network Science and Engineering, v. 11, n. 2, p. 1799-1809, 2024Tradução . . Disponível em: https://doi.org/10.1109/TNSE.2023.3331655. Acesso em: 11 nov. 2024.
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      Valejo, A. D. B., Althoff, P. E., Faleiros, T. de P., Rocha Filho, G. P., Yu-Tao, Z., Jianglong, Y., et al. (2024). Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks. IEEE Transactions on Network Science and Engineering, 11( 2), 1799-1809. doi:10.1109/TNSE.2023.3331655
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      Valejo ADB, Althoff PE, Faleiros T de P, Rocha Filho GP, Yu-Tao Z, Jianglong Y, Weiguang L, Liang Z. Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks [Internet]. IEEE Transactions on Network Science and Engineering. 2024 ; 11( 2): 1799-1809.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1109/TNSE.2023.3331655
    • Vancouver

      Valejo ADB, Althoff PE, Faleiros T de P, Rocha Filho GP, Yu-Tao Z, Jianglong Y, Weiguang L, Liang Z. Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks [Internet]. IEEE Transactions on Network Science and Engineering. 2024 ; 11( 2): 1799-1809.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1109/TNSE.2023.3331655
  • Source: Chaos, Solitons and Fractals. Unidade: IFSC

    Subjects: RECONHECIMENTO DE PADRÕES, FRACTAIS, FÍSICA COMPUTACIONAL, REDES COMPLEXAS

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      BENATTI, Alexandre e COSTA, Luciano da Fontoura. On the transient and equilibrium features of growing fractal complex networks. Chaos, Solitons and Fractals, v. 183, p. 114904-1-114904-7, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.chaos.2024.114904. Acesso em: 11 nov. 2024.
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      Benatti, A., & Costa, L. da F. (2024). On the transient and equilibrium features of growing fractal complex networks. Chaos, Solitons and Fractals, 183, 114904-1-114904-7. doi:10.1016/j.chaos.2024.114904
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      Benatti A, Costa L da F. On the transient and equilibrium features of growing fractal complex networks [Internet]. Chaos, Solitons and Fractals. 2024 ; 183 114904-1-114904-7.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.chaos.2024.114904
    • Vancouver

      Benatti A, Costa L da F. On the transient and equilibrium features of growing fractal complex networks [Internet]. Chaos, Solitons and Fractals. 2024 ; 183 114904-1-114904-7.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.chaos.2024.114904
  • Source: Physical Review E. Unidade: ICMC

    Subjects: PROCESSOS ESTOCÁSTICOS, REDES COMPLEXAS, SURTOS DE DOENÇAS

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      SILVA, Diogo Henrique da e RODRIGUES, Francisco Aparecido e FERREIRA, Silvio C. Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks. Physical Review E, v. 110, n. 1, p. 014302-1-014302-9, 2024Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.110.014302. Acesso em: 11 nov. 2024.
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      Silva, D. H. da, Rodrigues, F. A., & Ferreira, S. C. (2024). Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks. Physical Review E, 110( 1), 014302-1-014302-9. doi:10.1103/PhysRevE.110.014302
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      Silva DH da, Rodrigues FA, Ferreira SC. Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks [Internet]. Physical Review E. 2024 ; 110( 1): 014302-1-014302-9.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1103/PhysRevE.110.014302
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      Silva DH da, Rodrigues FA, Ferreira SC. Accuracy of discrete- and continuous-time mean-field theories for epidemic processes on complex networks [Internet]. Physical Review E. 2024 ; 110( 1): 014302-1-014302-9.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1103/PhysRevE.110.014302
  • Source: Journal of Physics : Complexity. Unidade: ICMC

    Subjects: REDES COMPLEXAS, COMÉRCIO INTERNACIONAL

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      SILVA, Thiago Christiano e WILHELM, Paulo Victor Berri e AMANCIO, Diego Raphael. Interconnectivity disrupted by fading globalization: a network approach to recent international trade developments. Journal of Physics : Complexity, v. 5, p. 1-19, 2024Tradução . . Disponível em: https://doi.org/10.1088/2632-072X/ad4dfc. Acesso em: 11 nov. 2024.
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      Silva, T. C., Wilhelm, P. V. B., & Amancio, D. R. (2024). Interconnectivity disrupted by fading globalization: a network approach to recent international trade developments. Journal of Physics : Complexity, 5, 1-19. doi:10.1088/2632-072X/ad4dfc
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      Silva TC, Wilhelm PVB, Amancio DR. Interconnectivity disrupted by fading globalization: a network approach to recent international trade developments [Internet]. Journal of Physics : Complexity. 2024 ; 5 1-19.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1088/2632-072X/ad4dfc
    • Vancouver

      Silva TC, Wilhelm PVB, Amancio DR. Interconnectivity disrupted by fading globalization: a network approach to recent international trade developments [Internet]. Journal of Physics : Complexity. 2024 ; 5 1-19.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1088/2632-072X/ad4dfc
  • Source: Scientometrics. Unidade: ICMC

    Subjects: REDES COMPLEXAS, PROCESSAMENTO DE LINGUAGEM NATURAL

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      TOHALINO, Jorge Andoni Valverde e SILVA, Thiago Christiano e AMANCIO, Diego Raphael. Using word embedding to detect keywords in texts modeled as complex networks. Scientometrics, v. 129, n. 7, p. 3599-3623, 2024Tradução . . Disponível em: https://doi.org/10.1007/s11192-024-05055-7. Acesso em: 11 nov. 2024.
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      Tohalino, J. A. V., Silva, T. C., & Amancio, D. R. (2024). Using word embedding to detect keywords in texts modeled as complex networks. Scientometrics, 129( 7), 3599-3623. doi:10.1007/s11192-024-05055-7
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      Tohalino JAV, Silva TC, Amancio DR. Using word embedding to detect keywords in texts modeled as complex networks [Internet]. Scientometrics. 2024 ; 129( 7): 3599-3623.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/s11192-024-05055-7
    • Vancouver

      Tohalino JAV, Silva TC, Amancio DR. Using word embedding to detect keywords in texts modeled as complex networks [Internet]. Scientometrics. 2024 ; 129( 7): 3599-3623.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/s11192-024-05055-7
  • Source: Knowledge and Information Systems. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), REDES COMPLEXAS, MERCADO FINANCEIRO

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      CASTILHO, Douglas et al. Forecasting financial market structure from network features using machine learning. Knowledge and Information Systems, v. 66, n. 8, p. 4497-4525, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10115-024-02095-6. Acesso em: 11 nov. 2024.
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      Castilho, D., Souza, T. T. P., Kang, S. M., Gama, J., & Carvalho, A. C. P. de L. F. de. (2024). Forecasting financial market structure from network features using machine learning. Knowledge and Information Systems, 66( 8), 4497-4525. doi:10.1007/s10115-024-02095-6
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      Castilho D, Souza TTP, Kang SM, Gama J, Carvalho ACP de LF de. Forecasting financial market structure from network features using machine learning [Internet]. Knowledge and Information Systems. 2024 ; 66( 8): 4497-4525.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/s10115-024-02095-6
    • Vancouver

      Castilho D, Souza TTP, Kang SM, Gama J, Carvalho ACP de LF de. Forecasting financial market structure from network features using machine learning [Internet]. Knowledge and Information Systems. 2024 ; 66( 8): 4497-4525.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/s10115-024-02095-6
  • Source: Physica A : statistical mechanics and its applications. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, COMÉRCIO INTERNACIONAL

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      SILVA, Thiago Christiano e WILHELM, Paulo Victor Berri e AMANCIO, Diego Raphael. Machine learning and economic forecasting: the role of international trade networks. Physica A : statistical mechanics and its applications, v. 649, p. 1-22, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2024.129977. Acesso em: 11 nov. 2024.
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      Silva, T. C., Wilhelm, P. V. B., & Amancio, D. R. (2024). Machine learning and economic forecasting: the role of international trade networks. Physica A : statistical mechanics and its applications, 649, 1-22. doi:10.1016/j.physa.2024.129977
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      Silva TC, Wilhelm PVB, Amancio DR. Machine learning and economic forecasting: the role of international trade networks [Internet]. Physica A : statistical mechanics and its applications. 2024 ; 649 1-22.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2024.129977
    • Vancouver

      Silva TC, Wilhelm PVB, Amancio DR. Machine learning and economic forecasting: the role of international trade networks [Internet]. Physica A : statistical mechanics and its applications. 2024 ; 649 1-22.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2024.129977
  • Source: Physica A. Unidades: IFSC, ICMC

    Subjects: REDES NEURAIS, RECONHECIMENTO DE PADRÕES, APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, TEXTURA

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      RIBAS, Lucas Correia et al. Color-texture classification based on spatio-spectral complex network representations. Physica A, v. 635, p. 129518-1-129518-15, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2024.129518. Acesso em: 11 nov. 2024.
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      Ribas, L. C., Scabini, L. F. dos S., Condori, R. H. M., & Bruno, O. M. (2024). Color-texture classification based on spatio-spectral complex network representations. Physica A, 635, 129518-1-129518-15. doi:10.1016/j.physa.2024.129518
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      Ribas LC, Scabini LF dos S, Condori RHM, Bruno OM. Color-texture classification based on spatio-spectral complex network representations [Internet]. Physica A. 2024 ; 635 129518-1-129518-15.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2024.129518
    • Vancouver

      Ribas LC, Scabini LF dos S, Condori RHM, Bruno OM. Color-texture classification based on spatio-spectral complex network representations [Internet]. Physica A. 2024 ; 635 129518-1-129518-15.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2024.129518
  • Source: Pattern Recognition. Unidades: IFSC, EP

    Subjects: REDES COMPLEXAS, REDES NEURAIS, VISÃO COMPUTACIONAL, TEXTURA

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      ZIELINSKI, Kallil Miguel Caparroz et al. A network classification method based on density time evolution patterns extracted from network automata. Pattern Recognition, v. 146, p. 109802-1-109802-13 + supplementary materials, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2023.109946. Acesso em: 11 nov. 2024.
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      Zielinski, K. M. C., Ribas, L. C., Machicao, J., & Bruno, O. M. (2024). A network classification method based on density time evolution patterns extracted from network automata. Pattern Recognition, 146, 109802-1-109802-13 + supplementary materials. doi:10.1016/j.patcog.2023.109946
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      Zielinski KMC, Ribas LC, Machicao J, Bruno OM. A network classification method based on density time evolution patterns extracted from network automata [Internet]. Pattern Recognition. 2024 ; 146 109802-1-109802-13 + supplementary materials.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109946
    • Vancouver

      Zielinski KMC, Ribas LC, Machicao J, Bruno OM. A network classification method based on density time evolution patterns extracted from network automata [Internet]. Pattern Recognition. 2024 ; 146 109802-1-109802-13 + supplementary materials.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109946
  • Source: Pattern Recognition. Unidade: IFSC

    Subjects: REDES COMPLEXAS, REDES NEURAIS, VISÃO COMPUTACIONAL, TEXTURA, RECONHECIMENTO DE PADRÕES

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      RIBAS, Lucas Correia e BRUNO, Odemir Martinez. Learning a complex network representation for shape classification. Pattern Recognition, v. 154, p. 110566-1-110566-10 + supplementary data, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2024.110566. Acesso em: 11 nov. 2024.
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      Ribas, L. C., & Bruno, O. M. (2024). Learning a complex network representation for shape classification. Pattern Recognition, 154, 110566-1-110566-10 + supplementary data. doi:10.1016/j.patcog.2024.110566
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      Ribas LC, Bruno OM. Learning a complex network representation for shape classification [Internet]. Pattern Recognition. 2024 ; 154 110566-1-110566-10 + supplementary data.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2024.110566
    • Vancouver

      Ribas LC, Bruno OM. Learning a complex network representation for shape classification [Internet]. Pattern Recognition. 2024 ; 154 110566-1-110566-10 + supplementary data.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2024.110566
  • Source: PLoS ONE. Unidade: ICMC

    Assunto: REDES COMPLEXAS

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      GUERREIRO, Lucas e SILVA, Filipi Nascimento e AMANCIO, Diego Raphael. Identifying the perceived local properties of networks reconstructed from biased random walks. PLoS ONE, v. 19, n. 1, p. 1-18, 2024Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0296088. Acesso em: 11 nov. 2024.
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      Guerreiro, L., Silva, F. N., & Amancio, D. R. (2024). Identifying the perceived local properties of networks reconstructed from biased random walks. PLoS ONE, 19( 1), 1-18. doi:10.1371/journal.pone.0296088
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      Guerreiro L, Silva FN, Amancio DR. Identifying the perceived local properties of networks reconstructed from biased random walks [Internet]. PLoS ONE. 2024 ; 19( 1): 1-18.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1371/journal.pone.0296088
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      Guerreiro L, Silva FN, Amancio DR. Identifying the perceived local properties of networks reconstructed from biased random walks [Internet]. PLoS ONE. 2024 ; 19( 1): 1-18.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1371/journal.pone.0296088
  • Source: Physica A : statistical mechanics and its applications. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, HEURÍSTICA

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      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: 11 nov. 2024.
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      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.2024.129618
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      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 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2024.129618
    • Vancouver

      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 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2024.129618
  • Source: Physics of Life Reviews. Unidade: ICMC

    Subjects: REDES COMPLEXAS, CÉREBRO

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      PERON, Thomas. The networkness of the brain: comment on “Does the brain behave like a (complex) network? I. Dynamics” by Papo and Buldú. Physics of Life Reviews, v. 49, p. 71-73, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.plrev.2023.12.006. Acesso em: 11 nov. 2024.
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      Peron, T. (2024). The networkness of the brain: comment on “Does the brain behave like a (complex) network? I. Dynamics” by Papo and Buldú. Physics of Life Reviews, 49, 71-73. doi:10.1016/j.plrev.2024.03.005
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      Peron T. The networkness of the brain: comment on “Does the brain behave like a (complex) network? I. Dynamics” by Papo and Buldú [Internet]. Physics of Life Reviews. 2024 ; 49 71-73.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.plrev.2023.12.006
    • Vancouver

      Peron T. The networkness of the brain: comment on “Does the brain behave like a (complex) network? I. Dynamics” by Papo and Buldú [Internet]. Physics of Life Reviews. 2024 ; 49 71-73.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.plrev.2023.12.006
  • Source: Physica A. Unidades: ICMC, FEA

    Subjects: REDES COMPLEXAS, FINANÇAS, ALGORITMOS GENÉTICOS

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      ALEXANDRE, Michel et al. Efficiency-stability trade-off in financial systems: a multi-objective optimization approach. Physica A, v. 629, p. 1-9, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2023.129213. Acesso em: 11 nov. 2024.
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      Alexandre, M., Michalak, K., Silva, T. C., & Rodrigues, F. A. (2023). Efficiency-stability trade-off in financial systems: a multi-objective optimization approach. Physica A, 629, 1-9. doi:10.1016/j.physa.2023.129213
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      Alexandre M, Michalak K, Silva TC, Rodrigues FA. Efficiency-stability trade-off in financial systems: a multi-objective optimization approach [Internet]. Physica A. 2023 ; 629 1-9.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2023.129213
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      Alexandre M, Michalak K, Silva TC, Rodrigues FA. Efficiency-stability trade-off in financial systems: a multi-objective optimization approach [Internet]. Physica A. 2023 ; 629 1-9.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.physa.2023.129213
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: VISUALIZAÇÃO, REDES COMPLEXAS

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      LINHARES, Claudio Douglas Gouveia et al. LargeNetVis: visual exploration of large temporal networks based on community taxonomies. IEEE Transactions on Visualization and Computer Graphics, v. 29, n. Ja 2023, p. 203-213, 2023Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2022.3209477. Acesso em: 11 nov. 2024.
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      Linhares, C. D. G., Ponciano, J. R., Pedro, D. S., Rocha, L. E. C. da, Traina, A. J. M., & Poco, J. (2023). LargeNetVis: visual exploration of large temporal networks based on community taxonomies. IEEE Transactions on Visualization and Computer Graphics, 29( Ja 2023), 203-213. doi:10.1109/TVCG.2022.3209477
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      Linhares CDG, Ponciano JR, Pedro DS, Rocha LEC da, Traina AJM, Poco J. LargeNetVis: visual exploration of large temporal networks based on community taxonomies [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 203-213.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1109/TVCG.2022.3209477
    • Vancouver

      Linhares CDG, Ponciano JR, Pedro DS, Rocha LEC da, Traina AJM, Poco J. LargeNetVis: visual exploration of large temporal networks based on community taxonomies [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 203-213.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1109/TVCG.2022.3209477
  • Source: Pattern Recognition. Unidade: IFSC

    Subjects: REDES COMPLEXAS, REDES NEURAIS, VISÃO COMPUTACIONAL, TEXTURA

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      SCABINI, Leonardo Felipe dos Santos et al. RADAM: texture recognition through randomized aggregated encoding of deep activation maps. Pattern Recognition, v. No 2023, p. 109802-1-109802-13 + supplementary materials, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2023.109802. Acesso em: 11 nov. 2024.
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      Scabini, L. F. dos S., Zielinski, K. M. C., Ribas, L. C., Gonçalves, W. N., Baets, B. D., & Bruno, O. M. (2023). RADAM: texture recognition through randomized aggregated encoding of deep activation maps. Pattern Recognition, No 2023, 109802-1-109802-13 + supplementary materials. doi:10.1016/j.patcog.2023.109802
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      Scabini LF dos S, Zielinski KMC, Ribas LC, Gonçalves WN, Baets BD, Bruno OM. RADAM: texture recognition through randomized aggregated encoding of deep activation maps [Internet]. Pattern Recognition. 2023 ; No 2023 109802-1-109802-13 + supplementary materials.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109802
    • Vancouver

      Scabini LF dos S, Zielinski KMC, Ribas LC, Gonçalves WN, Baets BD, Bruno OM. RADAM: texture recognition through randomized aggregated encoding of deep activation maps [Internet]. Pattern Recognition. 2023 ; No 2023 109802-1-109802-13 + supplementary materials.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109802
  • Source: Europhysics Letters. Unidades: ICMC, FEA

    Subjects: REDES COMPLEXAS, SISTEMA FINANCEIRO, DETERMINANTES

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      ALEXANDRE, Michel et al. The determinants of the individual nestedness contribution in financial systems. Europhysics Letters, v. 141, n. 4, p. 42001-p1-42001-p7, 2023Tradução . . Disponível em: https://doi.org/10.1209/0295-5075/acba42. Acesso em: 11 nov. 2024.
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      Alexandre, M., Xavier, F. J., Silva, T. C., & Rodrigues, F. A. (2023). The determinants of the individual nestedness contribution in financial systems. Europhysics Letters, 141( 4), 42001-p1-42001-p7. doi:10.1209/0295-5075/acba42
    • NLM

      Alexandre M, Xavier FJ, Silva TC, Rodrigues FA. The determinants of the individual nestedness contribution in financial systems [Internet]. Europhysics Letters. 2023 ; 141( 4): 42001-p1-42001-p7.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1209/0295-5075/acba42
    • Vancouver

      Alexandre M, Xavier FJ, Silva TC, Rodrigues FA. The determinants of the individual nestedness contribution in financial systems [Internet]. Europhysics Letters. 2023 ; 141( 4): 42001-p1-42001-p7.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1209/0295-5075/acba42
  • Source: European Journal of Operational Research. Unidade: ICMC

    Subjects: REDES COMPLEXAS, RISCO, FRAMEWORKS, FINANÇAS

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    • ABNT

      ALEXANDRE, Michel et al. Does the default pecking order impact systemic risk?: evidence from Brazilian data. European Journal of Operational Research, v. 309, p. 1379-1391, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.ejor.2023.01.043. Acesso em: 11 nov. 2024.
    • APA

      Alexandre, M., Silva, T. C., Michalak, K., & Rodrigues, F. A. (2023). Does the default pecking order impact systemic risk?: evidence from Brazilian data. European Journal of Operational Research, 309, 1379-1391. doi:10.1016/j.ejor.2023.01.043
    • NLM

      Alexandre M, Silva TC, Michalak K, Rodrigues FA. Does the default pecking order impact systemic risk?: evidence from Brazilian data [Internet]. European Journal of Operational Research. 2023 ; 309 1379-1391.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ejor.2023.01.043
    • Vancouver

      Alexandre M, Silva TC, Michalak K, Rodrigues FA. Does the default pecking order impact systemic risk?: evidence from Brazilian data [Internet]. European Journal of Operational Research. 2023 ; 309 1379-1391.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ejor.2023.01.043
  • Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), ENERGIA ELÉTRICA

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    • ABNT

      CASTILHO, Douglas et al. Feature selection using complex networks to support price trend forecast in energy markets. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191426. Acesso em: 11 nov. 2024.
    • APA

      Castilho, D., Santos, M. R. dos, Tinós, R., Carvalho, A. C. P. de L. F. de, Paula, M. B. S. de, Ladeira, L., et al. (2023). Feature selection using complex networks to support price trend forecast in energy markets. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191426
    • NLM

      Castilho D, Santos MR dos, Tinós R, Carvalho ACP de LF de, Paula MBS de, Ladeira L, Guarnier E, Silva Filho D, Suiama DY, Macedo Junior EA, Alipio LP. Feature selection using complex networks to support price trend forecast in energy markets [Internet]. Proceedings. 2023 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426
    • Vancouver

      Castilho D, Santos MR dos, Tinós R, Carvalho ACP de LF de, Paula MBS de, Ladeira L, Guarnier E, Silva Filho D, Suiama DY, Macedo Junior EA, Alipio LP. Feature selection using complex networks to support price trend forecast in energy markets [Internet]. Proceedings. 2023 ;[citado 2024 nov. 11 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426
  • Source: Information Sciences. Unidades: IFSC, ICMC

    Subjects: REDES COMPLEXAS, GEOMETRIA E MODELAGEM COMPUTACIONAL

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    • ABNT

      SOUZA, Bárbara Côrtes e et al. Text characterization based on recurrence networks. Information Sciences, v. 641, p. 119124-1-119124-15, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2023.119124. Acesso em: 11 nov. 2024.
    • APA

      Souza, B. C. e, Silva, F. N., Arruda, H. F. de, Silva, G. D. da, Costa, L. da F., & Amancio, D. R. (2023). Text characterization based on recurrence networks. Information Sciences, 641, 119124-1-119124-15. doi:10.1016/j.ins.2023.119124
    • NLM

      Souza BC e, Silva FN, Arruda HF de, Silva GD da, Costa L da F, Amancio DR. Text characterization based on recurrence networks [Internet]. Information Sciences. 2023 ; 641 119124-1-119124-15.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ins.2023.119124
    • Vancouver

      Souza BC e, Silva FN, Arruda HF de, Silva GD da, Costa L da F, Amancio DR. Text characterization based on recurrence networks [Internet]. Information Sciences. 2023 ; 641 119124-1-119124-15.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1016/j.ins.2023.119124

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