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  • Artigo de periodico

    Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks (2024)

    Valejo, Alan Demetrius Baria ; Althoff, Paulo Eduardo ; Faleiros, Thiago de Paulo ; Rocha Filho, Geraldo Pereira ; Yu-Tao, Zhu ; Jianglong, Yan; Weiguang, Liu; Liang, Zhao

    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: 06 out. 2024.

    • APA

      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

    • NLM

      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 out. 06 ] 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 out. 06 ] Available from: https://doi.org/10.1109/TNSE.2023.3331655

  • Artigo de periodico

    Systemic risk assessment using complex networks approach: evidence from the Brazilian (re)insurance market (2024)

    Carvalho, João Vinicius de França ; Guimarâes, Acássio Silva

    Source: Research in International Business and Finance. Unidade: FEA

    Subjects: RESSEGURO, RISCO (SEGURO), REDES COMPLEXAS

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      CARVALHO, João Vinicius de França e GUIMARÂES, Acássio Silva. Systemic risk assessment using complex networks approach: evidence from the Brazilian (re)insurance market. Research in International Business and Finance, v. 67, n. Ja 2024, 2024Tradução . . Disponível em: https://www.sciencedirect.com/science/article/pii/S0275531923001915. Acesso em: 06 out. 2024.

    • APA

      Carvalho, J. V. de F., & Guimarâes, A. S. (2024). Systemic risk assessment using complex networks approach: evidence from the Brazilian (re)insurance market. Research in International Business and Finance, 67( Ja 2024). doi:10.1016/j.ribaf.2023.102065

    • NLM

      Carvalho JV de F, Guimarâes AS. Systemic risk assessment using complex networks approach: evidence from the Brazilian (re)insurance market [Internet]. Research in International Business and Finance. 2024 ; 67( Ja 2024):[citado 2024 out. 06 ] Available from: https://www.sciencedirect.com/science/article/pii/S0275531923001915

    • Vancouver

      Carvalho JV de F, Guimarâes AS. Systemic risk assessment using complex networks approach: evidence from the Brazilian (re)insurance market [Internet]. Research in International Business and Finance. 2024 ; 67( Ja 2024):[citado 2024 out. 06 ] Available from: https://www.sciencedirect.com/science/article/pii/S0275531923001915

  • Artigo de periodico

    Identifying the perceived local properties of networks reconstructed from biased random walks (2024)

    Guerreiro, Lucas ; Silva, Filipi Nascimento ; Amancio, Diego Raphael

    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: 06 out. 2024.

    • APA

      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

    • NLM

      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 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0296088

    • Vancouver

      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 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0296088

  • Artigo de periodico

    LargeNetVis: visual exploration of large temporal networks based on community taxonomies (2023)

    Linhares, Claudio Douglas Gouveia ; Ponciano, Jean Roberto ; Pedro, Diogenes Silva; Rocha, Luis Enrique Correa da ; Traina, Agma Juci Machado ; Poco, Jorge

    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: 06 out. 2024.

    • APA

      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 out. 06 ] 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 out. 06 ] Available from: https://doi.org/10.1109/TVCG.2022.3209477

  • Trabalho de evento

    The strength of influence ties in stock networks: empirical analysis for portfolio selection (2023)

    Ambiel, Thiago ; Castilho, Douglas; Carvalho, André Carlos Ponce de Leon Ferreira de

    Source: Proceedings. Conference titles: IEEE International Conference on Data Mining Workshops - ICDMW. Unidade: ICMC

    Subjects: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, REDES COMPLEXAS, MERCADO FINANCEIRO

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      AMBIEL, Thiago e CASTILHO, Douglas e CARVALHO, André Carlos Ponce de Leon Ferreira de. The strength of influence ties in stock networks: empirical analysis for portfolio selection. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/ICDMW60847.2023.00066. Acesso em: 06 out. 2024.

    • APA

      Ambiel, T., Castilho, D., & Carvalho, A. C. P. de L. F. de. (2023). The strength of influence ties in stock networks: empirical analysis for portfolio selection. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICDMW60847.2023.00066

    • NLM

      Ambiel T, Castilho D, Carvalho ACP de LF de. The strength of influence ties in stock networks: empirical analysis for portfolio selection [Internet]. Proceedings. 2023 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/ICDMW60847.2023.00066

    • Vancouver

      Ambiel T, Castilho D, Carvalho ACP de LF de. The strength of influence ties in stock networks: empirical analysis for portfolio selection [Internet]. Proceedings. 2023 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/ICDMW60847.2023.00066

  • Trabalho de evento

    Complex network-based data classification using minimum spanning tree metric and optimization (2023)

    Saire, Josimar Edinson Chire ; Liang, Zhao

    Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL

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      SAIRE, Josimar Edinson Chire e LIANG, Zhao. Complex network-based data classification using minimum spanning tree metric and optimization. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191004. Acesso em: 06 out. 2024.

    • APA

      Saire, J. E. C., & Liang, Z. (2023). Complex network-based data classification using minimum spanning tree metric and optimization. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191004

    • NLM

      Saire JEC, Liang Z. Complex network-based data classification using minimum spanning tree metric and optimization [Internet]. Proceedings. 2023 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004

    • Vancouver

      Saire JEC, Liang Z. Complex network-based data classification using minimum spanning tree metric and optimization [Internet]. Proceedings. 2023 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004

  • Trabalho de evento

    Feature selection using complex networks to support price trend forecast in energy markets (2023)

    Castilho, Douglas; Santos, Moises Rocha dos ; Tinós, Renato ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Paula, Marcos Basile Saviano de; Ladeira, Lucas; Guarnier, Ewerton ; Silva Filho, Donato ; Suiama, Danilo Y; Macedo Junior, Edmur A; Alipio, Lucas P

    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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      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: 06 out. 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 out. 06 ] 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 out. 06 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426

  • Artigo de periodico

    Text characterization based on recurrence networks (2023)

    Souza, Bárbara Côrtes e ; Silva, Filipi Nascimento ; Arruda, Henrique Ferraz de ; Silva, Giovana Daniele da ; Costa, Luciano da Fontoura ; Amancio, Diego Raphael

    Source: Information Sciences. Unidades: IFSC, ICMC

    Subjects: REDES COMPLEXAS, GEOMETRIA E MODELAGEM COMPUTACIONAL

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      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: 06 out. 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 out. 06 ] 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 out. 06 ] Available from: https://doi.org/10.1016/j.ins.2023.119124

  • Artigo de periodico

    Using citation networks to evaluate the impact of text length on keyword extraction (2023)

    Tohalino, Jorge Andoni Valverde ; Silva, Thiago Christiano ; Amancio, Diego Raphael

    Source: PLoS ONE. Unidade: ICMC

    Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO, REDES COMPLEXAS

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      TOHALINO, Jorge Andoni Valverde e SILVA, Thiago Christiano e AMANCIO, Diego Raphael. Using citation networks to evaluate the impact of text length on keyword extraction. PLoS ONE, v. 18, n. 11, p. 1-17, 2023Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0294500. Acesso em: 06 out. 2024.

    • APA

      Tohalino, J. A. V., Silva, T. C., & Amancio, D. R. (2023). Using citation networks to evaluate the impact of text length on keyword extraction. PLoS ONE, 18( 11), 1-17. doi:10.1371/journal.pone.0294500

    • NLM

      Tohalino JAV, Silva TC, Amancio DR. Using citation networks to evaluate the impact of text length on keyword extraction [Internet]. PLoS ONE. 2023 ; 18( 11): 1-17.[citado 2024 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0294500

    • Vancouver

      Tohalino JAV, Silva TC, Amancio DR. Using citation networks to evaluate the impact of text length on keyword extraction [Internet]. PLoS ONE. 2023 ; 18( 11): 1-17.[citado 2024 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0294500

  • Trabalho de evento

    Data classification via centrality measures of complex networks (2023)

    Fernandes, Janayna M.; Suzuki, Guilherme M.; Zhao, Liang ; Carneiro, Murillo Guimarães

    Source: Proceedings. Conference titles: International Joint Conference on Neural Networks (IJCNN). Unidade: FFCLRP

    Subjects: MATEMÁTICA DA COMPUTAÇÃO, REDES COMPLEXAS, ALGORITMOS

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      FERNANDES, Janayna M. et al. Data classification via centrality measures of complex networks. 2023, Anais.. New York: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2023. Disponível em: https://ieeexplore.ieee.org/document/10192048. Acesso em: 06 out. 2024.

    • APA

      Fernandes, J. M., Suzuki, G. M., Zhao, L., & Carneiro, M. G. (2023). Data classification via centrality measures of complex networks. In Proceedings. New York: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Recuperado de https://ieeexplore.ieee.org/document/10192048

    • NLM

      Fernandes JM, Suzuki GM, Zhao L, Carneiro MG. Data classification via centrality measures of complex networks [Internet]. Proceedings. 2023 ;[citado 2024 out. 06 ] Available from: https://ieeexplore.ieee.org/document/10192048

    • Vancouver

      Fernandes JM, Suzuki GM, Zhao L, Carneiro MG. Data classification via centrality measures of complex networks [Internet]. Proceedings. 2023 ;[citado 2024 out. 06 ] Available from: https://ieeexplore.ieee.org/document/10192048

  • Artigo de periodico

    Complex network-based classification of radiographic images for COVID-19 diagnosis (2023)

    Weiguang, Liu; Rodrigues, Rafael Delalibera ; Jianglong, Yan; Yu-Tao, Zhu; Pereira, Everson José de Freitas; Gen, Li; Qiusheng, Zheng; Liang, Zhao

    Source: PLoS ONE. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, RADIOGRAFIA, COVID-19

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      WEIGUANG, Liu et al. Complex network-based classification of radiographic images for COVID-19 diagnosis. PLoS ONE, v. 18, n. 9, p. 1-26, 2023Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0290968. Acesso em: 06 out. 2024.

    • APA

      Weiguang, L., Rodrigues, R. D., Jianglong, Y., Yu-Tao, Z., Pereira, E. J. de F., Gen, L., et al. (2023). Complex network-based classification of radiographic images for COVID-19 diagnosis. PLoS ONE, 18( 9), 1-26. doi:10.1371/ journal.pone.0290968

    • NLM

      Weiguang L, Rodrigues RD, Jianglong Y, Yu-Tao Z, Pereira EJ de F, Gen L, Qiusheng Z, Liang Z. Complex network-based classification of radiographic images for COVID-19 diagnosis [Internet]. PLoS ONE. 2023 ; 18( 9): 1-26.[citado 2024 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0290968

    • Vancouver

      Weiguang L, Rodrigues RD, Jianglong Y, Yu-Tao Z, Pereira EJ de F, Gen L, Qiusheng Z, Liang Z. Complex network-based classification of radiographic images for COVID-19 diagnosis [Internet]. PLoS ONE. 2023 ; 18( 9): 1-26.[citado 2024 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0290968

  • Artigo de periodico

    First-passage process in degree space for the time-dependent Erdos-Rényi and Watts-Strogatz models (2022)

    Ampuero, Fernanda ; Hase, Masayuki Oka

    Source: Physical Review E: covering statistical, nonlinear, biological, and soft matter physics. Unidade: EACH

    Assunto: REDES COMPLEXAS

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      AMPUERO, Fernanda e HASE, Masayuki Oka. First-passage process in degree space for the time-dependent Erdos-Rényi and Watts-Strogatz models. Physical Review E: covering statistical, nonlinear, biological, and soft matter physics, v. 106, p. 01-07, 2022Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.106.034320. Acesso em: 06 out. 2024.

    • APA

      Ampuero, F., & Hase, M. O. (2022). First-passage process in degree space for the time-dependent Erdos-Rényi and Watts-Strogatz models. Physical Review E: covering statistical, nonlinear, biological, and soft matter physics, 106, 01-07. doi:10.1103/PhysRevE.106.034320

    • NLM

      Ampuero F, Hase MO. First-passage process in degree space for the time-dependent Erdos-Rényi and Watts-Strogatz models [Internet]. Physical Review E: covering statistical, nonlinear, biological, and soft matter physics. 2022 ; 106 01-07.[citado 2024 out. 06 ] Available from: https://doi.org/10.1103/PhysRevE.106.034320

    • Vancouver

      Ampuero F, Hase MO. First-passage process in degree space for the time-dependent Erdos-Rényi and Watts-Strogatz models [Internet]. Physical Review E: covering statistical, nonlinear, biological, and soft matter physics. 2022 ; 106 01-07.[citado 2024 out. 06 ] Available from: https://doi.org/10.1103/PhysRevE.106.034320

  • Artigo de periodico

    Clustered and deep echo state networks for signal noise reduction (2022)

    Oliveira Junior, Laercio de; Stelzer, Florian; Liang, Zhao

    Source: Machine Learning. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDES NEURAIS, SISTEMAS DINÂMICOS

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      OLIVEIRA JUNIOR, Laercio de e STELZER, Florian e LIANG, Zhao. Clustered and deep echo state networks for signal noise reduction. Machine Learning, v. 111, n. 8, p. 2885-2904, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10994-022-06135-6. Acesso em: 06 out. 2024.

    • APA

      Oliveira Junior, L. de, Stelzer, F., & Liang, Z. (2022). Clustered and deep echo state networks for signal noise reduction. Machine Learning, 111( 8), 2885-2904. doi:10.1007/s10994-022-06135-6

    • NLM

      Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2024 out. 06 ] Available from: https://doi.org/10.1007/s10994-022-06135-6

    • Vancouver

      Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2024 out. 06 ] Available from: https://doi.org/10.1007/s10994-022-06135-6

  • Artigo de periodico

    Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments (2022)

    Alves, Caroline Lourenço ; Cury, Rubens Gisbert ; Roster, Kirstin ; Pineda, Aruane Mello ; Rodrigues, Francisco Aparecido ; Thielemann, Christiane ; Ciba, Manuel

    Source: PLOS ONE. Unidades: ICMC, FM

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, ELETROENCEFALOGRAFIA

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      ALVES, Caroline Lourenço et al. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLOS ONE, v. 17, n. 12, p. 1-26, 2022Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0277257. Acesso em: 06 out. 2024.

    • APA

      Alves, C. L., Cury, R. G., Roster, K., Pineda, A. M., Rodrigues, F. A., Thielemann, C., & Ciba, M. (2022). Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLOS ONE, 17( 12), 1-26. doi:10.1371/journal.pone.0277257

    • NLM

      Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments [Internet]. PLOS ONE. 2022 ; 17( 12): 1-26.[citado 2024 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0277257

    • Vancouver

      Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments [Internet]. PLOS ONE. 2022 ; 17( 12): 1-26.[citado 2024 out. 06 ] Available from: https://doi.org/10.1371/journal.pone.0277257

  • Artigo de periodico

    Modelling how social network algorithms can influence opinion polarization (2022)

    Arruda, Henrique Ferraz de ; Cardoso, Felipe Maciel; Arruda, Guilherme Ferraz de; Hernández, Alexis R.; Costa, Luciano da Fontoura ; Moreno, Yamir

    Source: Information Sciences. Unidade: IFSC

    Subjects: REDES COMPLEXAS, GEOMETRIA E MODELAGEM COMPUTACIONAL

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      ARRUDA, Henrique Ferraz de et al. Modelling how social network algorithms can influence opinion polarization. Information Sciences, v. 588, p. 265-278 , 2022Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2021.12.069. Acesso em: 06 out. 2024.

    • APA

      Arruda, H. F. de, Cardoso, F. M., Arruda, G. F. de, Hernández, A. R., Costa, L. da F., & Moreno, Y. (2022). Modelling how social network algorithms can influence opinion polarization. Information Sciences, 588, 265-278 . doi:10.1016/j.ins.2021.12.069

    • NLM

      Arruda HF de, Cardoso FM, Arruda GF de, Hernández AR, Costa L da F, Moreno Y. Modelling how social network algorithms can influence opinion polarization [Internet]. Information Sciences. 2022 ; 588 265-278 .[citado 2024 out. 06 ] Available from: https://doi.org/10.1016/j.ins.2021.12.069

    • Vancouver

      Arruda HF de, Cardoso FM, Arruda GF de, Hernández AR, Costa L da F, Moreno Y. Modelling how social network algorithms can influence opinion polarization [Internet]. Information Sciences. 2022 ; 588 265-278 .[citado 2024 out. 06 ] Available from: https://doi.org/10.1016/j.ins.2021.12.069

  • Trabalho de evento

    A perceptual loss based complex neural beamforming for ambix 3D speech enhancement (2022)

    Guimarães, Heitor Rodrigues; Beccaro, Wesley; Arjona Ramírez, Miguel

    Source: L3DAS22: proceedings. Conference titles: Machine Learning for 3D Audio Signal Processing Virtual. Unidade: EP

    Subjects: APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, PROCESSAMENTO DE VOZ

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      GUIMARÃES, Heitor Rodrigues e BECCARO, Wesley e ARJONA RAMÍREZ, Miguel. A perceptual loss based complex neural beamforming for ambix 3D speech enhancement. 2022, Anais.. [S.l.: s.n.], 2022. Disponível em: https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf. Acesso em: 06 out. 2024.

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      Guimarães, H. R., Beccaro, W., & Arjona Ramírez, M. (2022). A perceptual loss based complex neural beamforming for ambix 3D speech enhancement. In L3DAS22: proceedings. [S.l.: s.n.]. Recuperado de https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf

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      Guimarães HR, Beccaro W, Arjona Ramírez M. A perceptual loss based complex neural beamforming for ambix 3D speech enhancement [Internet]. L3DAS22: proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf

    • Vancouver

      Guimarães HR, Beccaro W, Arjona Ramírez M. A perceptual loss based complex neural beamforming for ambix 3D speech enhancement [Internet]. L3DAS22: proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf

  • Trabalho de evento

    Combining clutter reduction methods for temporal network visualization (2022)

    Ponciano, Jean Roberto ; Linhares, Claudio Douglas Gouveia ; Rocha, Luis Enrique Correa da ; Faria, Elaine R ; Travençolo, Bruno Augusto Nassif

    Source: Proceedings. Conference titles: ACM/SIGAPP Symposium on Applied Computing - SAC. Unidade: ICMC

    Subjects: VISUALIZAÇÃO, REDES COMPLEXAS

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      PONCIANO, Jean Roberto et al. Combining clutter reduction methods for temporal network visualization. 2022, Anais.. New York: ACM, 2022. Disponível em: https://doi.org/10.1145/3477314.3507018. Acesso em: 06 out. 2024.

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      Ponciano, J. R., Linhares, C. D. G., Rocha, L. E. C. da, Faria, E. R., & Travençolo, B. A. N. (2022). Combining clutter reduction methods for temporal network visualization. In Proceedings. New York: ACM. doi:10.1145/3477314.3507018

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      Ponciano JR, Linhares CDG, Rocha LEC da, Faria ER, Travençolo BAN. Combining clutter reduction methods for temporal network visualization [Internet]. Proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1145/3477314.3507018

    • Vancouver

      Ponciano JR, Linhares CDG, Rocha LEC da, Faria ER, Travençolo BAN. Combining clutter reduction methods for temporal network visualization [Internet]. Proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1145/3477314.3507018

  • Trabalho de evento

    Complex texture features learned by applying randomized neural network on graphs (2022)

    Zielinski, Kallil M. C.; Ribas, Lucas Correia ; Scabini, Leonardo ; Bruno, Odemir Martinez

    Source: Proceedings. Conference titles: International Conference on Image Processing Theory, Tools and Applications - IPTA. Unidade: IFSC

    Subjects: REDES COMPLEXAS, IMAGEM DIGITAL (ANÁLISE), RECONHECIMENTO DE IMAGEM, RECONHECIMENTO DE PADRÕES, TEXTURA (ANÁLISE), INTELIGÊNCIA ARTIFICIAL

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      ZIELINSKI, Kallil M. C. et al. Complex texture features learned by applying randomized neural network on graphs. 2022, Anais.. Piscataway: Institute of Electrical and Electronic Engineers - IEEE, 2022. Disponível em: https://doi.org/10.1109/IPTA54936.2022.9784123. Acesso em: 06 out. 2024.

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      Zielinski, K. M. C., Ribas, L. C., Scabini, L., & Bruno, O. M. (2022). Complex texture features learned by applying randomized neural network on graphs. In Proceedings. Piscataway: Institute of Electrical and Electronic Engineers - IEEE. doi:10.1109/IPTA54936.2022.9784123

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      Zielinski KMC, Ribas LC, Scabini L, Bruno OM. Complex texture features learned by applying randomized neural network on graphs [Internet]. Proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/IPTA54936.2022.9784123

    • Vancouver

      Zielinski KMC, Ribas LC, Scabini L, Bruno OM. Complex texture features learned by applying randomized neural network on graphs [Internet]. Proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/IPTA54936.2022.9784123

  • Trabalho de evento

    A complex network approach for fish species recognition based on otolith shape (2022)

    Ribas, Lucas Correia ; Scabini, Leonardo ; Bruno, Odemir Martinez

    Source: Proceedings. Conference titles: International Conference on Image Processing Theory, Tools and Applications - IPTA. Unidade: IFSC

    Subjects: REDES COMPLEXAS, REDES NEURAIS, IMAGEM DIGITAL, RECONHECIMENTO DE IMAGEM, INTELIGÊNCIA ARTIFICIAL

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      RIBAS, Lucas Correia e SCABINI, Leonardo e BRUNO, Odemir Martinez. A complex network approach for fish species recognition based on otolith shape. 2022, Anais.. Piscataway: Institute of Electrical and Electronic Engineers - IEEE, 2022. Disponível em: https://doi.org/10.1109/IPTA54936.2022.9784114. Acesso em: 06 out. 2024.

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      Ribas, L. C., Scabini, L., & Bruno, O. M. (2022). A complex network approach for fish species recognition based on otolith shape. In Proceedings. Piscataway: Institute of Electrical and Electronic Engineers - IEEE. doi:10.1109/IPTA54936.2022.9784114

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      Ribas LC, Scabini L, Bruno OM. A complex network approach for fish species recognition based on otolith shape [Internet]. Proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/IPTA54936.2022.9784114

    • Vancouver

      Ribas LC, Scabini L, Bruno OM. A complex network approach for fish species recognition based on otolith shape [Internet]. Proceedings. 2022 ;[citado 2024 out. 06 ] Available from: https://doi.org/10.1109/IPTA54936.2022.9784114

  • Artigo de periodico

    A comparative analysis of knowledge acquisition performance in complex networks (2021)

    Guerreiro, Lucas; Silva, Filipi Nascimento ; Amancio, Diego Raphael

    Source: Information Sciences. Unidade: ICMC

    Subjects: REDES COMPLEXAS, DESCOBERTA DE CONHECIMENTO

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      GUERREIRO, Lucas e SILVA, Filipi Nascimento e AMANCIO, Diego Raphael. A comparative analysis of knowledge acquisition performance in complex networks. Information Sciences, v. 555, p. 46-57, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2020.12.060. Acesso em: 06 out. 2024.

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      Guerreiro, L., Silva, F. N., & Amancio, D. R. (2021). A comparative analysis of knowledge acquisition performance in complex networks. Information Sciences, 555, 46-57. doi:10.1016/j.ins.2020.12.060

    • NLM

      Guerreiro L, Silva FN, Amancio DR. A comparative analysis of knowledge acquisition performance in complex networks [Internet]. Information Sciences. 2021 ; 555 46-57.[citado 2024 out. 06 ] Available from: https://doi.org/10.1016/j.ins.2020.12.060

    • Vancouver

      Guerreiro L, Silva FN, Amancio DR. A comparative analysis of knowledge acquisition performance in complex networks [Internet]. Information Sciences. 2021 ; 555 46-57.[citado 2024 out. 06 ] Available from: https://doi.org/10.1016/j.ins.2020.12.060

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