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  • Source: European Physical Journal - Special Topics. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, SISTEMAS DINÂMICOS, ALGORITMOS ÚTEIS E ESPECÍFICOS

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      VERRI, Filipe Alves Neto; GUELERI, Roberto Alves; QIUSHENG, Zheng; JUNBAO, Zhang; LIANG, Zhao. Network community detection via iterative edge removal in a flocking-like system. European Physical Journal - Special Topics, Heidelberg, v. 230, n. 14-15, p. 2843-2855, 2021. Disponível em: < https://doi.org/10.1140/epjs/s11734-021-00154-5 > DOI: 10.1140/epjs/s11734-021-00154-5.
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      Verri, F. A. N., Gueleri, R. A., Qiusheng, Z., Junbao, Z., & Liang, Z. (2021). Network community detection via iterative edge removal in a flocking-like system. European Physical Journal - Special Topics, 230( 14-15), 2843-2855. doi:10.1140/epjs/s11734-021-00154-5
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      Verri FAN, Gueleri RA, Qiusheng Z, Junbao Z, Liang Z. Network community detection via iterative edge removal in a flocking-like system [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2843-2855.Available from: https://doi.org/10.1140/epjs/s11734-021-00154-5
    • Vancouver

      Verri FAN, Gueleri RA, Qiusheng Z, Junbao Z, Liang Z. Network community detection via iterative edge removal in a flocking-like system [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2843-2855.Available from: https://doi.org/10.1140/epjs/s11734-021-00154-5
  • Source: The European Physical Journal Special Topics. Unidade: FFCLRP

    Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS

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      VALEJO, Alan Demetrius Baria; SANTOS, Wellington de Oliveira dos; NALDI, Murilo Coelho; LIANG, Zhao. A review and comparative analysis of coarsening algorithms on bipartite networks. The European Physical Journal Special Topics, Heidelberg, 2021. Disponível em: < https://doi.org/10.1140/epjs/s11734-021-00159-0 > DOI: 10.1140/epjs/s11734-021-00159-0.
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      Valejo, A. D. B., Santos, W. de O. dos, Naldi, M. C., & Liang, Z. (2021). A review and comparative analysis of coarsening algorithms on bipartite networks. The European Physical Journal Special Topics. doi:10.1140/epjs/s11734-021-00159-0
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      Valejo ADB, Santos W de O dos, Naldi MC, Liang Z. A review and comparative analysis of coarsening algorithms on bipartite networks [Internet]. The European Physical Journal Special Topics. 2021 ;Available from: https://doi.org/10.1140/epjs/s11734-021-00159-0
    • Vancouver

      Valejo ADB, Santos W de O dos, Naldi MC, Liang Z. A review and comparative analysis of coarsening algorithms on bipartite networks [Internet]. The European Physical Journal Special Topics. 2021 ;Available from: https://doi.org/10.1140/epjs/s11734-021-00159-0
  • Source: European Physical Journal - Special Topics. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES

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      ANGHINONI, Leandro; VEGA-OLIVEROS, Didier Augusto; SILVA, Thiago Christiano; LIANG, Zhao. Time series pattern identification by hierarchical community detection. European Physical Journal - Special Topics, Heidelberg, v. 230, n. 14-15, p. 2775-2782, 2021. Disponível em: < https://doi.org/10.1140/epjs/s11734-021-00163-4 > DOI: 10.1140/epjs/s11734-021-00163-4.
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      Anghinoni, L., Vega-Oliveros, D. A., Silva, T. C., & Liang, Z. (2021). Time series pattern identification by hierarchical community detection. European Physical Journal - Special Topics, 230( 14-15), 2775-2782. doi:10.1140/epjs/s11734-021-00163-4
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      Anghinoni L, Vega-Oliveros DA, Silva TC, Liang Z. Time series pattern identification by hierarchical community detection [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2775-2782.Available from: https://doi.org/10.1140/epjs/s11734-021-00163-4
    • Vancouver

      Anghinoni L, Vega-Oliveros DA, Silva TC, Liang Z. Time series pattern identification by hierarchical community detection [Internet]. European Physical Journal - Special Topics. 2021 ; 230( 14-15): 2775-2782.Available from: https://doi.org/10.1140/epjs/s11734-021-00163-4
  • Source: IEEE Transactions on Neural Networks and Learning Systems. Unidade: FFCLRP

    Subjects: PROBABILIDADE, DISSEMINAÇÃO SELETIVA DA INFORMAÇÃO, REDES COMPLEXAS, EDITORES DE LIGAÇÃO

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      VEGA-OLIVEROS, Didier Augusto; LIANG, Zhao; ROCHA, Anderson; BERTON, Lilian. Link prediction based on stochastic information diffusion. IEEE Transactions on Neural Networks and Learning Systems, Piscataway, 2021. Disponível em: < https://doi.org/10.1109/TNNLS.2021.3053263 > DOI: 10.1109/TNNLS.2021.3053263.
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      Vega-Oliveros, D. A., Liang, Z., Rocha, A., & Berton, L. (2021). Link prediction based on stochastic information diffusion. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2021.3053263
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      Vega-Oliveros DA, Liang Z, Rocha A, Berton L. Link prediction based on stochastic information diffusion [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2021 ;Available from: https://doi.org/10.1109/TNNLS.2021.3053263
    • Vancouver

      Vega-Oliveros DA, Liang Z, Rocha A, Berton L. Link prediction based on stochastic information diffusion [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2021 ;Available from: https://doi.org/10.1109/TNNLS.2021.3053263
  • Source: Natural Computing. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, BOLSA DE VALORES

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      COLLIRI, Tiago Santos; LIANG, Zhao. Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, Dordrecht, v. 20, n. 4, p. 791-804, 2021. Disponível em: < https://doi.org/10.1007/s11047-020-09829-9 > DOI: 10.1007/s11047-020-09829-9.
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      Colliri, T. S., & Liang, Z. (2021). Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, 20( 4), 791-804. doi:10.1007/s11047-020-09829-9
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      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ; 20( 4): 791-804.Available from: https://doi.org/10.1007/s11047-020-09829-9
    • Vancouver

      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ; 20( 4): 791-804.Available from: https://doi.org/10.1007/s11047-020-09829-9
  • Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDES NEURAIS, COMPUTAÇÃO APLICADA, ANÁLISE DE SÉRIES TEMPORAIS

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      OLIVEIRA JUNIOR, Laercio de; LIANG, Zhao. Clustered Echo State networks for signal denoising and frequency filtering. 2020.Universidade de São Paulo, Ribeirão Preto, 2020. Disponível em: < https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/ >.
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      Oliveira Junior, L. de, & Liang, Z. (2020). Clustered Echo State networks for signal denoising and frequency filtering. Universidade de São Paulo, Ribeirão Preto. Recuperado de https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/
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      Oliveira Junior L de, Liang Z. Clustered Echo State networks for signal denoising and frequency filtering [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/
    • Vancouver

      Oliveira Junior L de, Liang Z. Clustered Echo State networks for signal denoising and frequency filtering [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/
  • Source: Proceedings. Conference title: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, RECONHECIMENTO DE PADRÕES

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      COLLIRI, Tiago Santos; WEIGUANG, Liu; LIANG, Zhao. An optimized modularity-based high level classification model. Anais.. Piscataway: IEEE, 2020.Disponível em: DOI: 10.1109/IJCNN48605.2020.9206755.
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      Colliri, T. S., Weiguang, L., & Liang, Z. (2020). An optimized modularity-based high level classification model. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9206755
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      Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755
    • Vancouver

      Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755
  • Source: Neurocomputing. Unidades: FFCLRP, ICMC

    Subjects: TURISMO, MEMÓRIA (ELETRÔNICA DIGITAL), ATRATORES

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      RODRIGUES, Rafael Delalibera; LIANG, Zhao; ZHENG, Qiusheng; ZHANG, Junbao. A tourist walk approach for internal and external outlier detection. Neurocomputing, Amsterdam, v. 393, p. 203-213, 2020. Disponível em: < https://doi.org/10.1016/j.neucom.2018.10.113 > DOI: 10.1016/j.neucom.2018.10.113.
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      Rodrigues, R. D., Liang, Z., Zheng, Q., & Zhang, J. (2020). A tourist walk approach for internal and external outlier detection. Neurocomputing, 393, 203-213. doi:10.1016/j.neucom.2018.10.113
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      Rodrigues RD, Liang Z, Zheng Q, Zhang J. A tourist walk approach for internal and external outlier detection [Internet]. Neurocomputing. 2020 ; 393 203-213.Available from: https://doi.org/10.1016/j.neucom.2018.10.113
    • Vancouver

      Rodrigues RD, Liang Z, Zheng Q, Zhang J. A tourist walk approach for internal and external outlier detection [Internet]. Neurocomputing. 2020 ; 393 203-213.Available from: https://doi.org/10.1016/j.neucom.2018.10.113
  • Source: Agência FAPESP. Unidade: FFCLRP

    Subjects: EQUIPAMENTO DE PROTEÇÃO INDIVIDUAL, COVID-19, SURTOS DE DOENÇAS, QUARENTENA

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      LIANG, Zhao. Quarentena e uso de máscara reduziram em 15% o contágio da COVID-19 em SP no início da epidemia. [Depoimento a Elton Alisson]. Agência FAPESP[S.l: s.n.], 2020.Disponível em: .
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      Liang, Z. (2020). Quarentena e uso de máscara reduziram em 15% o contágio da COVID-19 em SP no início da epidemia. [Depoimento a Elton Alisson]. Agência FAPESP. São Paulo. Recuperado de https://agencia.fapesp.br/quarentena-e-uso-de-mascara-reduziram-em-15-o-contagio-da-covid-19-em-sp-no-inicio-da-epidemia/33549/
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      Liang Z. Quarentena e uso de máscara reduziram em 15% o contágio da COVID-19 em SP no início da epidemia. [Depoimento a Elton Alisson] [Internet]. Agência FAPESP. 2020 ;Available from: https://agencia.fapesp.br/quarentena-e-uso-de-mascara-reduziram-em-15-o-contagio-da-covid-19-em-sp-no-inicio-da-epidemia/33549/
    • Vancouver

      Liang Z. Quarentena e uso de máscara reduziram em 15% o contágio da COVID-19 em SP no início da epidemia. [Depoimento a Elton Alisson] [Internet]. Agência FAPESP. 2020 ;Available from: https://agencia.fapesp.br/quarentena-e-uso-de-mascara-reduziram-em-15-o-contagio-da-covid-19-em-sp-no-inicio-da-epidemia/33549/
  • Source: Proceedings. Conference title: International Joint Conference on Neural Networks - IJCNN. Unidade: FFCLRP

    Subjects: MENSAGEM, CHAT, CRIPTOLOGIA, PRIVACIDADE, FRAMEWORKS

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      COTACALLAPA, Moshe; QUILES, Marcos Gonçalves; LIANG, Zhao; et al. Measuring the engagement level in encrypted group conversations by using temporal networks. Anais.. Los Alamitos: [s.n.], 2020.Disponível em: DOI: 10.1109/IJCNN48605.2020.9207174.
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      Cotacallapa, M., Quiles, M. G., Liang, Z., Macau, E. E. N., Vega-Oliveros, D. A., Berton, L., & Ferreira, L. N. (2020). Measuring the engagement level in encrypted group conversations by using temporal networks. In Proceedings. Los Alamitos. doi:10.1109/IJCNN48605.2020.9207174
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      Cotacallapa M, Quiles MG, Liang Z, Macau EEN, Vega-Oliveros DA, Berton L, Ferreira LN. Measuring the engagement level in encrypted group conversations by using temporal networks [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/IJCNN48605.2020.9207174
    • Vancouver

      Cotacallapa M, Quiles MG, Liang Z, Macau EEN, Vega-Oliveros DA, Berton L, Ferreira LN. Measuring the engagement level in encrypted group conversations by using temporal networks [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/IJCNN48605.2020.9207174
  • Source: Nature Communications. Unidade: FFCLRP

    Subjects: VALORES ATÍPICOS, ANÁLISE MULTIVARIADA, ANÁLISE DE SÉRIES TEMPORAIS

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      FERREIRA, Leonardo N.; VEGA-OLIVEROS, Didier Augusto; COTACALLAPA, Moshé; et al. Spatiotemporal data analysis with chronological networks. Nature Communications, London, v. 11, 2020. Disponível em: < https://doi.org/10.1038/s41467-020-17634-2 > DOI: 10.1038/s41467-020-17634-2.
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      Ferreira, L. N., Vega-Oliveros, D. A., Cotacallapa, M., Cardoso, M. F., Quiles, M. G., Macau, E. E. N., & Liang, Z. (2020). Spatiotemporal data analysis with chronological networks. Nature Communications, 11. doi:10.1038/s41467-020-17634-2
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      Ferreira LN, Vega-Oliveros DA, Cotacallapa M, Cardoso MF, Quiles MG, Macau EEN, Liang Z. Spatiotemporal data analysis with chronological networks [Internet]. Nature Communications. 2020 ; 11Available from: https://doi.org/10.1038/s41467-020-17634-2
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      Ferreira LN, Vega-Oliveros DA, Cotacallapa M, Cardoso MF, Quiles MG, Macau EEN, Liang Z. Spatiotemporal data analysis with chronological networks [Internet]. Nature Communications. 2020 ; 11Available from: https://doi.org/10.1038/s41467-020-17634-2
  • Source: Proceedings. Conference title: International Conference of Digital Transformation and Innovation Technology - Incodtrin. Unidade: FFCLRP

    Subjects: ALGORITMOS, MATEMÁTICA APLICADA, APRENDIZADO COMPUTACIONAL

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      ZUÑIGA, Esteban Wilfredo Vilca; LIANG, Zhao. A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions. Anais.. Manchester: [s.n.], 2020.Disponível em: .
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      Zuñiga, E. W. V., & Liang, Z. (2020). A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions. In Proceedings. Manchester. Recuperado de https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions
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      Zuñiga EWV, Liang Z. A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions [Internet]. Proceedings. 2020 ;Available from: https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions
    • Vancouver

      Zuñiga EWV, Liang Z. A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions [Internet]. Proceedings. 2020 ;Available from: https://www.researchgate.net/publication/344411081_A_new_network-base_high-level_data_classification_methodology_Quipus_by_modeling_attribute-attribute_interactions
  • Source: Scientific Reports. Unidades: FFCLRP, ICMC

    Subjects: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES

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      GAO, Xubo; ZHENG, Qiusheng; VEGA-OLIVEROS, Didier Augusto; ANGHINONI, Leandro; LIANG, Zhao. Temporal network pattern identification by community modelling. Scientific Reports, London, v. 10, p. 1-12, 2020. Disponível em: < https://doi.org/10.1038/s41598-019-57123-1 > DOI: 10.1038/s41598-019-57123-1.
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      Gao, X., Zheng, Q., Vega-Oliveros, D. A., Anghinoni, L., & Liang, Z. (2020). Temporal network pattern identification by community modelling. Scientific Reports, 10, 1-12. doi:10.1038/s41598-019-57123-1
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      Gao X, Zheng Q, Vega-Oliveros DA, Anghinoni L, Liang Z. Temporal network pattern identification by community modelling [Internet]. Scientific Reports. 2020 ; 10 1-12.Available from: https://doi.org/10.1038/s41598-019-57123-1
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      Gao X, Zheng Q, Vega-Oliveros DA, Anghinoni L, Liang Z. Temporal network pattern identification by community modelling [Internet]. Scientific Reports. 2020 ; 10 1-12.Available from: https://doi.org/10.1038/s41598-019-57123-1
  • Source: Lecture Notes in Artificial Intelligence. Conference title: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, ICMC

    Subject: REDES COMPLEXAS

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      MARTINS, Luan Vinicius Carvalho; LIANG, Zhao. Particle competition for unbalanced community detection in complex networks. Lecture Notes in Artificial Intelligence[S.l: s.n.], 2020.Disponível em: DOI: 10.1007/978-3-030-61380-8_22.
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      Martins, L. V. C., & Liang, Z. (2020). Particle competition for unbalanced community detection in complex networks. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_22
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      Martins LVC, Liang Z. Particle competition for unbalanced community detection in complex networks [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 322-336.Available from: https://doi.org/10.1007/978-3-030-61380-8_22
    • Vancouver

      Martins LVC, Liang Z. Particle competition for unbalanced community detection in complex networks [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 322-336.Available from: https://doi.org/10.1007/978-3-030-61380-8_22
  • Unidade: ICMC

    Subjects: REDES COMPLEXAS, DINÂMICA ESTOCÁSTICA, COMPUTAÇÃO BIOINSPIRADA

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      MARTINS, Luan Vinicius de Carvalho; LIANG, Zhao. A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks. 2020.Universidade de São Paulo, São Carlos, 2020. Disponível em: < https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/ >.
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      Martins, L. V. de C., & Liang, Z. (2020). A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks. Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/
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      Martins LV de C, Liang Z. A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/
    • Vancouver

      Martins LV de C, Liang Z. A Two-Stage Particle Competition Model for Unbalanced Community Detection in Complex Networks [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-20082020-101929/
  • Source: Revista Galileu. Unidade: FFCLRP

    Subjects: COVID-19, SURTOS DE DOENÇAS, QUARENTENA, EQUIPAMENTO DE PROTEÇÃO INDIVIDUAL

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      LIANG, Zhao. Quarentena e máscara reduziram contágio de Covid-19 em São Paulo e Brasília. [Depoimento a Elton Alisson]. Revista Galileu[S.l: s.n.], 2020.Disponível em: .
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      Liang, Z. (2020). Quarentena e máscara reduziram contágio de Covid-19 em São Paulo e Brasília. [Depoimento a Elton Alisson]. Revista Galileu. São Paulo. Recuperado de https://revistagalileu.globo.com/Ciencia/Saude/noticia/2020/07/quarentena-e-mascara-reduziram-contagio-de-covid-19-em-sao-paulo-e-brasilia.html
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      Liang Z. Quarentena e máscara reduziram contágio de Covid-19 em São Paulo e Brasília. [Depoimento a Elton Alisson] [Internet]. Revista Galileu. 2020 ;Available from: https://revistagalileu.globo.com/Ciencia/Saude/noticia/2020/07/quarentena-e-mascara-reduziram-contagio-de-covid-19-em-sao-paulo-e-brasilia.html
    • Vancouver

      Liang Z. Quarentena e máscara reduziram contágio de Covid-19 em São Paulo e Brasília. [Depoimento a Elton Alisson] [Internet]. Revista Galileu. 2020 ;Available from: https://revistagalileu.globo.com/Ciencia/Saude/noticia/2020/07/quarentena-e-mascara-reduziram-contagio-de-covid-19-em-sao-paulo-e-brasilia.html
  • Source: Proceedings. Conference title: Symposium on Knowledge Discovery, Mining and Learning - KDMiLe. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, REDES NEURAIS

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      OLIVEIRA JUNIOR, Laercio de; STELZER, Florian; LIANG, Zhao. Clustered echo state networks for signal observation and frequency filtering. Anais.. Porto Alegre: [s.n.], 2020.Disponível em: DOI: 10.5753/kdmile.2020.11955.
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      Oliveira Junior, L. de, Stelzer, F., & Liang, Z. (2020). Clustered echo state networks for signal observation and frequency filtering. In Proceedings. Porto Alegre. doi:10.5753/kdmile.2020.11955
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      Oliveira Junior L de, Stelzer F, Liang Z. Clustered echo state networks for signal observation and frequency filtering [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.5753/kdmile.2020.11955
    • Vancouver

      Oliveira Junior L de, Stelzer F, Liang Z. Clustered echo state networks for signal observation and frequency filtering [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.5753/kdmile.2020.11955
  • Unidade: FFCLRP

    Subjects: COVID-19, REDES COMPLEXAS, DIAGNÓSTICO POR IMAGEM, INTELIGÊNCIA ARTIFICIAL, RAIOS X, TÓRAX

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      PEREIRA, Everson José de Freitas; LIANG, Zhao. Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas. 2020.Universidade de São Paulo, Ribeirão Preto, 2020. Disponível em: < https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/ >.
    • APA

      Pereira, E. J. de F., & Liang, Z. (2020). Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas. Universidade de São Paulo, Ribeirão Preto. Recuperado de https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/
    • NLM

      Pereira EJ de F, Liang Z. Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/
    • Vancouver

      Pereira EJ de F, Liang Z. Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/
  • Source: Anais. Conference title: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC. Unidade: FFCLRP

    Subjects: MATEMÁTICA APLICADA, ALGORITMOS, APRENDIZADO COMPUTACIONAL

    Online source accessDOIHow to cite
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    • ABNT

      ZUÑIGA, Esteban Wilfredo Vilca; LIANG, Zhao. A network-based high-level data classification algorithm using betweenness centrality. Anais.. Porto Alegre: [s.n.], 2020.Disponível em: DOI: 10.5753/eniac.2020.12128.
    • APA

      Zuñiga, E. W. V., & Liang, Z. (2020). A network-based high-level data classification algorithm using betweenness centrality. In Anais. Porto Alegre. doi:10.5753/eniac.2020.12128
    • NLM

      Zuñiga EWV, Liang Z. A network-based high-level data classification algorithm using betweenness centrality [Internet]. Anais. 2020 ;Available from: https://doi.org/10.5753/eniac.2020.12128
    • Vancouver

      Zuñiga EWV, Liang Z. A network-based high-level data classification algorithm using betweenness centrality [Internet]. Anais. 2020 ;Available from: https://doi.org/10.5753/eniac.2020.12128
  • Source: Lecture Notes in Artificial Intelligence. Conference title: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: ICMC, FFCLRP

    Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, COVID-19, REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL

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    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      COLLIRI, Tiago Santos; DELBEM, Alexandre Cláudio Botazzo; LIANG, Zhao. Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network. Lecture Notes in Artificial Intelligence[S.l: s.n.], 2020.Disponível em: DOI: 10.1007/978-3-030-61380-8_27.
    • APA

      Colliri, T. S., Delbem, A. C. B., & Liang, Z. (2020). Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_27
    • NLM

      Colliri TS, Delbem ACB, Liang Z. Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 397-411.Available from: https://doi.org/10.1007/978-3-030-61380-8_27
    • Vancouver

      Colliri TS, Delbem ACB, Liang Z. Predicting the evolution of COVID-19 cases and deaths through a correlations-based temporal network [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 397-411.Available from: https://doi.org/10.1007/978-3-030-61380-8_27

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