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Artigo de periodico
SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level (2022)
Yuan, Jun ; Chan, Gromit Yeuk-Yin ; Barr, Brian; Overton, Kyle; Rees, Kim; Nonato, Luis Gustavo ; Bertini, Enrico ; Silva, Claudio Teixeira
Source: IEEE Computer Graphics and Applications. Unidade: ICMC
Subjects: CLUSTERS, VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
YUAN, Jun et al. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level. IEEE Computer Graphics and Applications, v. 42, n. 6, p. 24-36, 2022Tradução . . Disponível em: https://doi.org/10.1109/MCG.2022.3199727. Acesso em: 29 set. 2024.
APA
Yuan, J., Chan, G. Y. -Y., Barr, B., Overton, K., Rees, K., Nonato, L. G., et al. (2022). SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level. IEEE Computer Graphics and Applications, 42( 6), 24-36. doi:10.1109/MCG.2022.3199727
NLM
Yuan J, Chan GY-Y, Barr B, Overton K, Rees K, Nonato LG, Bertini E, Silva CT. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level [Internet]. IEEE Computer Graphics and Applications. 2022 ; 42( 6): 24-36.[citado 2024 set. 29 ] Available from: https://doi.org/10.1109/MCG.2022.3199727
Vancouver
Yuan J, Chan GY-Y, Barr B, Overton K, Rees K, Nonato LG, Bertini E, Silva CT. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level [Internet]. IEEE Computer Graphics and Applications. 2022 ; 42( 6): 24-36.[citado 2024 set. 29 ] Available from: https://doi.org/10.1109/MCG.2022.3199727
Artigo de periodico
CriPAV: street-level crime patterns analysis and visualization (2022)
Garcia-Zanabria, Germain ; Raimundo, Marcos M. M; Poco, Jorge ; Nery, Marcelo Batista ; Silva, Claudio T ; Adorno, Sérgio ; Nonato, Luis Gustavo
Source: IEEE Transactions on Visualization and Computer Graphics. Unidades: IEA, FFLCH, ICMC
Subjects: CRIMINALIDADE, ANÁLISE DE SÉRIES TEMPORAIS, ESPAÇO URBANO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GARCIA-ZANABRIA, Germain et al. CriPAV: street-level crime patterns analysis and visualization. IEEE Transactions on Visualization and Computer Graphics, v. 28, n. 12, p. 4000-4015, 2022Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2021.3111146. Acesso em: 29 set. 2024.
APA
Garcia-Zanabria, G., Raimundo, M. M. M., Poco, J., Nery, M. B., Silva, C. T., Adorno, S., & Nonato, L. G. (2022). CriPAV: street-level crime patterns analysis and visualization. IEEE Transactions on Visualization and Computer Graphics, 28( 12), 4000-4015. doi:10.1109/TVCG.2021.3111146
NLM
Garcia-Zanabria G, Raimundo MMM, Poco J, Nery MB, Silva CT, Adorno S, Nonato LG. CriPAV: street-level crime patterns analysis and visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2022 ; 28( 12): 4000-4015.[citado 2024 set. 29 ] Available from: https://doi.org/10.1109/TVCG.2021.3111146
Vancouver
Garcia-Zanabria G, Raimundo MMM, Poco J, Nery MB, Silva CT, Adorno S, Nonato LG. CriPAV: street-level crime patterns analysis and visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2022 ; 28( 12): 4000-4015.[citado 2024 set. 29 ] Available from: https://doi.org/10.1109/TVCG.2021.3111146
Artigo de periodico
NE-Motion: visual analysis of stroke patients using motion sensor networks (2021)
Contreras, Rodrigo Colnago ; Parnandi, Avinash ; Coelho, Bruno Gomes ; Silva, Claudio ; Schambra, Heidi ; Nonato, Luis Gustavo
Source: Sensors. Unidade: ICMC
Subjects: TEORIA DOS CONJUNTOS, VISUALIZAÇÃO, ACIDENTE VASCULAR CEREBRAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CONTRERAS, Rodrigo Colnago et al. NE-Motion: visual analysis of stroke patients using motion sensor networks. Sensors, v. 21, p. 1-22, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21134482. Acesso em: 29 set. 2024.
APA
Contreras, R. C., Parnandi, A., Coelho, B. G., Silva, C., Schambra, H., & Nonato, L. G. (2021). NE-Motion: visual analysis of stroke patients using motion sensor networks. Sensors, 21, 1-22. doi:10.3390/s21134482
NLM
Contreras RC, Parnandi A, Coelho BG, Silva C, Schambra H, Nonato LG. NE-Motion: visual analysis of stroke patients using motion sensor networks [Internet]. Sensors. 2021 ; 21 1-22.[citado 2024 set. 29 ] Available from: https://doi.org/10.3390/s21134482
Vancouver
Contreras RC, Parnandi A, Coelho BG, Silva C, Schambra H, Nonato LG. NE-Motion: visual analysis of stroke patients using motion sensor networks [Internet]. Sensors. 2021 ; 21 1-22.[citado 2024 set. 29 ] Available from: https://doi.org/10.3390/s21134482
Artigo de periodico
TopoMap: a 0-dimensional homology preserving projection of high-dimensional data (2021)
Doraiswamy, Harish ; Tierny, Julien ; Silva, Paulo J. S. ; Nonato, Luis Gustavo ; Silva, Claudio
Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC
Subjects: TOPOLOGIA, ANÁLISE DE DADOS, PROJEÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DORAISWAMY, Harish et al. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 2, p. 561-571, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2020.3030441. Acesso em: 29 set. 2024.
APA
Doraiswamy, H., Tierny, J., Silva, P. J. S., Nonato, L. G., & Silva, C. (2021). TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, 27( 2), 561-571. doi:10.1109/TVCG.2020.3030441
NLM
Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2024 set. 29 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441
Vancouver
Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2024 set. 29 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441
Artigo de periodico
Revealing dynamics, communities, and criticality from data (2020)
Eroglu, Deniz ; Tanzi, Matteo ; Strien, Sebastian van ; Pereira, Tiago
Source: Physical Review X. Unidade: ICMC
Subjects: REDES COMPLEXAS, ANÁLISE DE SÉRIES TEMPORAIS, PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
EROGLU, Deniz et al. Revealing dynamics, communities, and criticality from data. Physical Review X, v. 10, n. 2, p. 021047-1-021047-14, 2020Tradução . . Disponível em: https://doi.org/10.1103/PhysRevX.10.021047. Acesso em: 29 set. 2024.
APA
Eroglu, D., Tanzi, M., Strien, S. van, & Pereira, T. (2020). Revealing dynamics, communities, and criticality from data. Physical Review X, 10( 2), 021047-1-021047-14. doi:10.1103/PhysRevX.10.021047
NLM
Eroglu D, Tanzi M, Strien S van, Pereira T. Revealing dynamics, communities, and criticality from data [Internet]. Physical Review X. 2020 ; 10( 2): 021047-1-021047-14.[citado 2024 set. 29 ] Available from: https://doi.org/10.1103/PhysRevX.10.021047
Vancouver
Eroglu D, Tanzi M, Strien S van, Pereira T. Revealing dynamics, communities, and criticality from data [Internet]. Physical Review X. 2020 ; 10( 2): 021047-1-021047-14.[citado 2024 set. 29 ] Available from: https://doi.org/10.1103/PhysRevX.10.021047

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