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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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ABNT
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: 14 jul. 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 jul. 14 ] 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 jul. 14 ] Available from: https://doi.org/10.1109/TNSE.2023.3331655
Trabalho de evento
TransGNN: a transductive graph neural network with graph dynamic embedding (2023)
Anghinoni, Leandro ; Yu-Tao, Zhu; Donghong, Ji; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS
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ABNT
ANGHINONI, Leandro et al. TransGNN: a transductive graph neural network with graph dynamic embedding. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191134. Acesso em: 14 jul. 2024.
APA
Anghinoni, L., Yu-Tao, Z., Donghong, J., & Liang, Z. (2023). TransGNN: a transductive graph neural network with graph dynamic embedding. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191134
NLM
Anghinoni L, Yu-Tao Z, Donghong J, Liang Z. TransGNN: a transductive graph neural network with graph dynamic embedding [Internet]. Proceedings. 2023 ;[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191134
Vancouver
Anghinoni L, Yu-Tao Z, Donghong J, Liang Z. TransGNN: a transductive graph neural network with graph dynamic embedding [Internet]. Proceedings. 2023 ;[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191134
Trabalho de evento
WSI2ML: an open-source whole slide image annotation software for machine learning applications (2023)
Martins, Luan Vinicius de Carvalho ; Bueno, Adriana Passos ; Defelicibus, Alexandre ; Drummond, Rodrigo Duarte ; Valieris, Renan ; Yu-Tao, Zhu ; Silva, Israel Tojal da ; Liang, Zhao
Source: Proceedings. Conference titles: Brazilian Symposium on Multimedia and the Web - WebMedia. Unidades: FFCLRP, ICMC
Subjects: BIOINFORMÁTICA, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, PATOLOGIA CLÍNICA, TECNOLOGIAS DA SAÚDE
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MARTINS, Luan Vinicius de Carvalho et al. WSI2ML: an open-source whole slide image annotation software for machine learning applications. 2023, Anais.. New York: ACM, 2023. Disponível em: https://doi.org/10.1145/3617023.3617038. Acesso em: 14 jul. 2024.
APA
Martins, L. V. de C., Bueno, A. P., Defelicibus, A., Drummond, R. D., Valieris, R., Yu-Tao, Z., et al. (2023). WSI2ML: an open-source whole slide image annotation software for machine learning applications. In Proceedings. New York: ACM. doi:10.1145/3617023.3617038
NLM
Martins LV de C, Bueno AP, Defelicibus A, Drummond RD, Valieris R, Yu-Tao Z, Silva IT da, Liang Z. WSI2ML: an open-source whole slide image annotation software for machine learning applications [Internet]. Proceedings. 2023 ;[citado 2024 jul. 14 ] Available from: https://doi.org/10.1145/3617023.3617038
Vancouver
Martins LV de C, Bueno AP, Defelicibus A, Drummond RD, Valieris R, Yu-Tao Z, Silva IT da, Liang Z. WSI2ML: an open-source whole slide image annotation software for machine learning applications [Internet]. Proceedings. 2023 ;[citado 2024 jul. 14 ] Available from: https://doi.org/10.1145/3617023.3617038
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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ABNT
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: 14 jul. 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 jul. 14 ] 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 jul. 14 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191004
Artigo de periodico
TOE:: a grid-tagging discontinuous ner model enhanced by embedding tag/word relations and more fine-grained tags (2023)
Liu, Jiang; Ji, Donghong; Li, Jingye; Xie, Dongdong; Teng, Chong; Zhao, Liang; Li, Fei
Source: IEEE/ACM Transactions on Audio, Speech, and Language Processing. Unidade: FFCLRP
Subjects: DESIGNS (CONFIGURAÇÕES COMBINATÓRIAS), ARQUITETURA E ORGANIZAÇÃO DE COMPUTADORES, PROCESSAMENTO DE LINGUAGEM NATURAL
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ABNT
LIU, Jiang et al. TOE:: a grid-tagging discontinuous ner model enhanced by embedding tag/word relations and more fine-grained tags. IEEE/ACM Transactions on Audio, Speech, and Language Processing, v. 31, p. 177-187, 2023Tradução . . Disponível em: https://doi.org/10.1109/TASLP.2022.3221009. Acesso em: 14 jul. 2024.
APA
Liu, J., Ji, D., Li, J., Xie, D., Teng, C., Zhao, L., & Li, F. (2023). TOE:: a grid-tagging discontinuous ner model enhanced by embedding tag/word relations and more fine-grained tags. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 31, 177-187. doi:10.1109/TASLP.2022.3221009
NLM
Liu J, Ji D, Li J, Xie D, Teng C, Zhao L, Li F. TOE:: a grid-tagging discontinuous ner model enhanced by embedding tag/word relations and more fine-grained tags [Internet]. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2023 ; 31 177-187.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/TASLP.2022.3221009
Vancouver
Liu J, Ji D, Li J, Xie D, Teng C, Zhao L, Li F. TOE:: a grid-tagging discontinuous ner model enhanced by embedding tag/word relations and more fine-grained tags [Internet]. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2023 ; 31 177-187.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/TASLP.2022.3221009
Trabalho de evento
High-level classification for EEG analysis (2023)
Carneiro, Murillo Guimarães; Ramos, Camila D.; Destro Filho, João Batista; Zhu, Yu-tao; Ji, Donghong; Liang, Zhao
Conference titles: International Joint Conference on Neural Networks. Unidade: FFCLRP
Subjects: REDES COMPLEXAS, SISTEMA BINÁRIO, ELETROENCEFALOGRAFIA, PROGNÓSTICO, COMA
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ABNT
CARNEIRO, Murillo Guimarães et al. High-level classification for EEG analysis. 2023, Anais.. Queensland: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2023. p. 1-8. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191823. Acesso em: 14 jul. 2024.
APA
Carneiro, M. G., Ramos, C. D., Destro Filho, J. B., Zhu, Y. -tao, Ji, D., & Liang, Z. (2023). High-level classification for EEG analysis. In (p. 1-8). Queensland: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/IJCNN54540.2023.10191823
NLM
Carneiro MG, Ramos CD, Destro Filho JB, Zhu Y-tao, Ji D, Liang Z. High-level classification for EEG analysis [Internet]. 2023 ; 1-8.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191823
Vancouver
Carneiro MG, Ramos CD, Destro Filho JB, Zhu Y-tao, Ji D, Liang Z. High-level classification for EEG analysis [Internet]. 2023 ; 1-8.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191823
Trabalho de evento-anais periodico
Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach (2023)
Zuñiga, Esteban Wilfredo Vilca ; Ranieri, Caetano Mazzoni ; Zhao, Liang ; Ueyama, Jó ; Zhu, Yu-tao; Ji, Donghong
Source: Proceedings. Conference titles: International Neural Network Society Workshop on Deep Learning Innovations and Applications - INNS DLIA. Unidades: FFCLRP, ICMC
Subjects: DINHEIRO ELETRÔNICO, APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, INVESTIMENTOS, LUCRO
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ZUÑIGA, Esteban Wilfredo Vilca et al. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.procs.2023.08.192. Acesso em: 14 jul. 2024. , 2023
APA
Zuñiga, E. W. V., Ranieri, C. M., Zhao, L., Ueyama, J., Zhu, Y. -tao, & Ji, D. (2023). Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. doi:10.1016/j.procs.2023.08.192
NLM
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192
Vancouver
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192
Artigo de periodico
Characterizing data patterns with core-periphery network modeling (2023)
Jianglong, Yan; Anghinoni, Leandro ; Yu-Tao, Zhu; Weiguang, Liu; Gen, Li; Qiusheng, Zheng; Liang, Zhao
Source: Journal of Computational Science. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, RADIOGRAFIA, COVID-19
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ABNT
JIANGLONG, Yan et al. Characterizing data patterns with core-periphery network modeling. Journal of Computational Science, v. 66, n. Ja 2023, p. 1-13, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.jocs.2022.101912. Acesso em: 14 jul. 2024.
APA
Jianglong, Y., Anghinoni, L., Yu-Tao, Z., Weiguang, L., Gen, L., Qiusheng, Z., & Liang, Z. (2023). Characterizing data patterns with core-periphery network modeling. Journal of Computational Science, 66( Ja 2023), 1-13. doi:10.1016/j.jocs.2022.101912
NLM
Jianglong Y, Anghinoni L, Yu-Tao Z, Weiguang L, Gen L, Qiusheng Z, Liang Z. Characterizing data patterns with core-periphery network modeling [Internet]. Journal of Computational Science. 2023 ; 66( Ja 2023): 1-13.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.jocs.2022.101912
Vancouver
Jianglong Y, Anghinoni L, Yu-Tao Z, Weiguang L, Gen L, Qiusheng Z, Liang Z. Characterizing data patterns with core-periphery network modeling [Internet]. Journal of Computational Science. 2023 ; 66( Ja 2023): 1-13.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.jocs.2022.101912
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: 14 jul. 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 jul. 14 ] 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 jul. 14 ] Available from: https://doi.org/10.1371/journal.pone.0290968
Artigo de periodico
Amplified signal response by cluster synchronization competition in rings with short-distance couplings (2022)
Liang, Xiaoming; Hua, Lei; Zhang, Xiyun; Liang, Zhao
Source: Physical Review E. Unidade: FFCLRP
Subjects: AMPLIFICADORES ÓPTICOS, SISTEMAS NÃO LINEARES, TOPOLOGIA EM COMPUTAÇÃO
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LIANG, Xiaoming et al. Amplified signal response by cluster synchronization competition in rings with short-distance couplings. Physical Review E, v. 106, n. 6, 2022Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.106.064306. Acesso em: 14 jul. 2024.
APA
Liang, X., Hua, L., Zhang, X., & Liang, Z. (2022). Amplified signal response by cluster synchronization competition in rings with short-distance couplings. Physical Review E, 106( 6). doi:10.1103/PhysRevE.106.064306
NLM
Liang X, Hua L, Zhang X, Liang Z. Amplified signal response by cluster synchronization competition in rings with short-distance couplings [Internet]. Physical Review E. 2022 ; 106( 6):[citado 2024 jul. 14 ] Available from: https://doi.org/10.1103/PhysRevE.106.064306
Vancouver
Liang X, Hua L, Zhang X, Liang Z. Amplified signal response by cluster synchronization competition in rings with short-distance couplings [Internet]. Physical Review E. 2022 ; 106( 6):[citado 2024 jul. 14 ] Available from: https://doi.org/10.1103/PhysRevE.106.064306
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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ABNT
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: 14 jul. 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 jul. 14 ] 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 jul. 14 ] Available from: https://doi.org/10.1007/s10994-022-06135-6
Artigo de periodico
OneEE: a one-stage framework for fast overlapping and nested event extraction (2022)
Cao, Hu; Li, Jingye; Su, Fangfang; Li, Fei; Fei, Hao; Wu, Shengqiong; Li, Bobo; Liang, Zhao; Ji, Donghong
Source: arXiv. Unidade: FFCLRP
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE PADRÕES, REPRESENTAÇÃO ORDINÁRIA
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CAO, Hu et al. OneEE: a one-stage framework for fast overlapping and nested event extraction. arXiv, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.48550/arXiv.2209.02693. Acesso em: 14 jul. 2024.
APA
Cao, H., Li, J., Su, F., Li, F., Fei, H., Wu, S., et al. (2022). OneEE: a one-stage framework for fast overlapping and nested event extraction. arXiv, 1-13. doi:10.48550/arXiv.2209.02693
NLM
Cao H, Li J, Su F, Li F, Fei H, Wu S, Li B, Liang Z, Ji D. OneEE: a one-stage framework for fast overlapping and nested event extraction [Internet]. arXiv. 2022 ; 1-13.[citado 2024 jul. 14 ] Available from: https://doi.org/10.48550/arXiv.2209.02693
Vancouver
Cao H, Li J, Su F, Li F, Fei H, Wu S, Li B, Liang Z, Ji D. OneEE: a one-stage framework for fast overlapping and nested event extraction [Internet]. arXiv. 2022 ; 1-13.[citado 2024 jul. 14 ] Available from: https://doi.org/10.48550/arXiv.2209.02693
Artigo de periodico
Multilevel coarsening for interactive visualization of large bipartite networks (2022)
Valejo, Alan Demetrius Baria ; Fabbri, Renato ; Lopes, Alneu de Andrade ; Liang, Zhao; Oliveira, Maria Cristina Ferreira de
Source: Frontiers in Research Metrics and Analytics. Unidades: ICMC, FFCLRP
Subjects: REDES COMPLEXAS, TEORIA DOS GRAFOS, VISUALIZAÇÃO
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VALEJO, Alan Demetrius Baria et al. Multilevel coarsening for interactive visualization of large bipartite networks. Frontiers in Research Metrics and Analytics, v. 7, p. 1-18, 2022Tradução . . Disponível em: https://doi.org/10.3389/frma.2022.855165. Acesso em: 14 jul. 2024.
APA
Valejo, A. D. B., Fabbri, R., Lopes, A. de A., Liang, Z., & Oliveira, M. C. F. de. (2022). Multilevel coarsening for interactive visualization of large bipartite networks. Frontiers in Research Metrics and Analytics, 7, 1-18. doi:10.3389/frma.2022.855165
NLM
Valejo ADB, Fabbri R, Lopes A de A, Liang Z, Oliveira MCF de. Multilevel coarsening for interactive visualization of large bipartite networks [Internet]. Frontiers in Research Metrics and Analytics. 2022 ; 7 1-18.[citado 2024 jul. 14 ] Available from: https://doi.org/10.3389/frma.2022.855165
Vancouver
Valejo ADB, Fabbri R, Lopes A de A, Liang Z, Oliveira MCF de. Multilevel coarsening for interactive visualization of large bipartite networks [Internet]. Frontiers in Research Metrics and Analytics. 2022 ; 7 1-18.[citado 2024 jul. 14 ] Available from: https://doi.org/10.3389/frma.2022.855165
Trabalho de evento-anais periodico
Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling (2021)
Yan, Jianglong; Liu, Weiguang; Zhu, Yu-tao; Li, Gen; Zheng, Qiusheng; Liang, Zhao
Source: Complex Networks & Their Applications X. Conference titles: International Conference on Complex Networks and Their Applications. Unidade: FFCLRP
Subjects: COVID-19, RAIOS X, IMAGEM DIGITAL, DADOS CATEGORIZADOS
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ABNT
YAN, Jianglong et al. Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling. Complex Networks & Their Applications X. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-93409-5_4. Acesso em: 14 jul. 2024. , 2021
APA
Yan, J., Liu, W., Zhu, Y. -tao, Li, G., Zheng, Q., & Liang, Z. (2021). Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling. Complex Networks & Their Applications X. Cham: Springer. doi:10.1007/978-3-030-93409-5_4
NLM
Yan J, Liu W, Zhu Y-tao, Li G, Zheng Q, Liang Z. Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling [Internet]. Complex Networks & Their Applications X. 2021 ; 1 40-49.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_4
Vancouver
Yan J, Liu W, Zhu Y-tao, Li G, Zheng Q, Liang Z. Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling [Internet]. Complex Networks & Their Applications X. 2021 ; 1 40-49.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_4
Artigo de periodico
Network community detection via iterative edge removal in a flocking-like system (2021)
Verri, Filipe Alves Neto ; Gueleri, Roberto Alves ; Qiusheng, Zheng; Junbao, Zhang; Liang, Zhao
Source: European Physical Journal - Special Topics. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, SISTEMAS DINÂMICOS, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
VERRI, Filipe Alves Neto et al. Network community detection via iterative edge removal in a flocking-like system. European Physical Journal - Special Topics, v. 230, n. 14-15, p. 2843-2855, 2021Tradução . . Disponível em: https://doi.org/10.1140/epjs/s11734-021-00154-5. Acesso em: 14 jul. 2024.
APA
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
NLM
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.[citado 2024 jul. 14 ] 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.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00154-5
Artigo de periodico
A review and comparative analysis of coarsening algorithms on bipartite networks (2021)
Valejo, Alan Demetrius Baria ; Santos, Wellington de Oliveira dos; Naldi, Murilo Coelho ; Liang, Zhao
Source: The European Physical Journal Special Topics. Unidade: FFCLRP
Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VALEJO, Alan Demetrius Baria et al. A review and comparative analysis of coarsening algorithms on bipartite networks. The European Physical Journal Special Topics, v. 230, n. 14-15, p. 2801 - 2811, 2021Tradução . . Disponível em: https://doi.org/10.1140/epjs/s11734-021-00159-0. Acesso em: 14 jul. 2024.
APA
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, 230( 14-15), 2801 - 2811. doi:10.1140/epjs/s11734-021-00159-0
NLM
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 ; 230( 14-15): 2801 - 2811.[citado 2024 jul. 14 ] 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 ; 230( 14-15): 2801 - 2811.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00159-0
Parte de monografia/livro
Classificação de Dados de Alto Nível em Redes Complexas (2021)
Liang, Zhao; Silva, Thiago Christiano ; Carneiro, Murillo Guimarães
Source: Inteligência artificial: avanços e tendências. Unidade: FFCLRP
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIANG, Zhao e SILVA, Thiago Christiano e CARNEIRO, Murillo Guimarães. Classificação de Dados de Alto Nível em Redes Complexas. Inteligência artificial: avanços e tendências. Tradução . São Paulo: Instituto de Estudos Avançados, 2021. p. 414 . Disponível em: https://doi.org/10.11606/9786587773131. Acesso em: 14 jul. 2024.
APA
Liang, Z., Silva, T. C., & Carneiro, M. G. (2021). Classificação de Dados de Alto Nível em Redes Complexas. In Inteligência artificial: avanços e tendências (p. 414 ). São Paulo: Instituto de Estudos Avançados. doi:10.11606/9786587773131
NLM
Liang Z, Silva TC, Carneiro MG. Classificação de Dados de Alto Nível em Redes Complexas [Internet]. In: Inteligência artificial: avanços e tendências. São Paulo: Instituto de Estudos Avançados; 2021. p. 414 .[citado 2024 jul. 14 ] Available from: https://doi.org/10.11606/9786587773131
Vancouver
Liang Z, Silva TC, Carneiro MG. Classificação de Dados de Alto Nível em Redes Complexas [Internet]. In: Inteligência artificial: avanços e tendências. São Paulo: Instituto de Estudos Avançados; 2021. p. 414 .[citado 2024 jul. 14 ] Available from: https://doi.org/10.11606/9786587773131
Artigo de periodico
Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach (2021)
Colliri, Tiago; Minakawa, Marcia Michie; Liang, Zhao
Source: Lecture Notes in Computer Science. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, FSP
Subjects: REDES COMPLEXAS, COVID-19, PROGNÓSTICO, BIOMARCADORES, CONTAGEM DE CÉLULAS SANGUÍNEAS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COLLIRI, Tiago e MINAKAWA, Marcia Michie e LIANG, Zhao. Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach. Lecture Notes in Computer Science, v. 13074, p. 42-57, 2021Tradução . . Disponível em: https://doi.org/10.1007/978-3-030-91699-2_4. Acesso em: 14 jul. 2024.
APA
Colliri, T., Minakawa, M. M., & Liang, Z. (2021). Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach. Lecture Notes in Computer Science, 13074, 42-57. doi:10.1007/978-3-030-91699-2_4
NLM
Colliri T, Minakawa MM, Liang Z. Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach [Internet]. Lecture Notes in Computer Science. 2021 ; 13074 42-57.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_4
Vancouver
Colliri T, Minakawa MM, Liang Z. Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach [Internet]. Lecture Notes in Computer Science. 2021 ; 13074 42-57.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_4
Artigo de periodico
Time series pattern identification by hierarchical community detection (2021)
Anghinoni, Leandro ; Vega-Oliveros, Didier Augusto ; Silva, Thiago Christiano ; Liang, Zhao
Source: European Physical Journal - Special Topics. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANGHINONI, Leandro et al. Time series pattern identification by hierarchical community detection. European Physical Journal - Special Topics, v. 230, n. 14-15, p. 2775-2782, 2021Tradução . . Disponível em: https://doi.org/10.1140/epjs/s11734-021-00163-4. Acesso em: 14 jul. 2024.
APA
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
NLM
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.[citado 2024 jul. 14 ] 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.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1140/epjs/s11734-021-00163-4
Artigo de periodico
Link prediction based on stochastic information diffusion (2021)
Vega-Oliveros, Didier Augusto ; Liang, Zhao ; Rocha, Anderson; Berton, Lilian
Source: IEEE Transactions on Neural Networks and Learning Systems. Unidade: FFCLRP
Subjects: PROBABILIDADE, DISSEMINAÇÃO SELETIVA DA INFORMAÇÃO, REDES COMPLEXAS, EDITORES DE LIGAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VEGA-OLIVEROS, Didier Augusto et al. Link prediction based on stochastic information diffusion. IEEE Transactions on Neural Networks and Learning Systems, 2021Tradução . . Disponível em: https://doi.org/10.1109/TNNLS.2021.3053263. Acesso em: 14 jul. 2024.
APA
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
NLM
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 ;[citado 2024 jul. 14 ] 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 ;[citado 2024 jul. 14 ] Available from: https://doi.org/10.1109/TNNLS.2021.3053263

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