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CASTELO, Antonio et al. A generalized combinatorial marching hypercube algorithm. Computational and Applied Mathematics, v. 43, p. 1-23, 2024Tradução . . Disponível em: https://doi.org/10.1007/s40314-024-02627-4. Acesso em: 04 set. 2024.
APA
Castelo, A., Nakassima, G. K., Bueno, L. M., & Gameiro, M. F. (2024). A generalized combinatorial marching hypercube algorithm. Computational and Applied Mathematics, 43, 1-23. doi:10.1007/s40314-024-02627-4
NLM
Castelo A, Nakassima GK, Bueno LM, Gameiro MF. A generalized combinatorial marching hypercube algorithm [Internet]. Computational and Applied Mathematics. 2024 ; 43 1-23.[citado 2024 set. 04 ] Available from: https://doi.org/10.1007/s40314-024-02627-4
Vancouver
Castelo A, Nakassima GK, Bueno LM, Gameiro MF. A generalized combinatorial marching hypercube algorithm [Internet]. Computational and Applied Mathematics. 2024 ; 43 1-23.[citado 2024 set. 04 ] Available from: https://doi.org/10.1007/s40314-024-02627-4
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BEDIA, Elizbeth Chipa e CANCHO, Vicente Garibay e BANDYOPADHYAY, Dipankar. A frailty model for semi-competing risk data with applications to colon cancer. Journal of the Indian Society for Probability and Statistics, v. 25, p. 395-416, 2024Tradução . . Disponível em: https://doi.org/10.1007/s41096-024-00186-9. Acesso em: 04 set. 2024.
APA
Bedia, E. C., Cancho, V. G., & Bandyopadhyay, D. (2024). A frailty model for semi-competing risk data with applications to colon cancer. Journal of the Indian Society for Probability and Statistics, 25, 395-416. doi:10.1007/s41096-024-00186-9
NLM
Bedia EC, Cancho VG, Bandyopadhyay D. A frailty model for semi-competing risk data with applications to colon cancer [Internet]. Journal of the Indian Society for Probability and Statistics. 2024 ; 25 395-416.[citado 2024 set. 04 ] Available from: https://doi.org/10.1007/s41096-024-00186-9
Vancouver
Bedia EC, Cancho VG, Bandyopadhyay D. A frailty model for semi-competing risk data with applications to colon cancer [Internet]. Journal of the Indian Society for Probability and Statistics. 2024 ; 25 395-416.[citado 2024 set. 04 ] Available from: https://doi.org/10.1007/s41096-024-00186-9
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VIEIRA, Ewerton R et al. Data-efficient characterization of the global dynamics of robot controllers with confidence guarantees. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/ICRA48891.2023.10160428. Acesso em: 04 set. 2024.
APA
Vieira, E. R., Sivaramakrishnan, A., Song, Y., Granados, E., Gameiro, M. F., Mischaikow, K., et al. (2023). Data-efficient characterization of the global dynamics of robot controllers with confidence guarantees. In Proceedings. Piscataway: IEEE. doi:10.1109/ICRA48891.2023.10160428
NLM
Vieira ER, Sivaramakrishnan A, Song Y, Granados E, Gameiro MF, Mischaikow K, Hung Y, Bekris KE. Data-efficient characterization of the global dynamics of robot controllers with confidence guarantees [Internet]. Proceedings. 2023 ;[citado 2024 set. 04 ] Available from: https://doi.org/10.1109/ICRA48891.2023.10160428
Vancouver
Vieira ER, Sivaramakrishnan A, Song Y, Granados E, Gameiro MF, Mischaikow K, Hung Y, Bekris KE. Data-efficient characterization of the global dynamics of robot controllers with confidence guarantees [Internet]. Proceedings. 2023 ;[citado 2024 set. 04 ] Available from: https://doi.org/10.1109/ICRA48891.2023.10160428
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SOARES, Andrey Coatrini et al. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, v. 451, n. Ja 2023, p. 138523-1-138523-9, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.cej.2022.138523. Acesso em: 04 set. 2024.
APA
Soares, A. C., Soares, J. C., Popolin Neto, M., Mello, S. S. de, Pinto, D. D. S. C., Carvalho, W. A., et al. (2023). Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, 451( Ja 2023), 138523-1-138523-9. doi:10.1016/j.cej.2022.138523
NLM
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Pinto DDSC, Carvalho WA, Gilmore MS, Piazzetta MH de O, Gobbi AL, Brandão H de M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models [Internet]. Chemical Engineering Journal. 2023 ; 451( Ja 2023): 138523-1-138523-9.[citado 2024 set. 04 ] Available from: https://doi.org/10.1016/j.cej.2022.138523
Vancouver
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Pinto DDSC, Carvalho WA, Gilmore MS, Piazzetta MH de O, Gobbi AL, Brandão H de M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models [Internet]. Chemical Engineering Journal. 2023 ; 451( Ja 2023): 138523-1-138523-9.[citado 2024 set. 04 ] Available from: https://doi.org/10.1016/j.cej.2022.138523
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BOLLT, Erik et al. Fractal basins as a mechanism for the nimble brain. Scientific Reports, v. 13, p. 1-11, 2023Tradução . . Disponível em: https://doi.org/10.1038/s41598-023-45664-5. Acesso em: 04 set. 2024.
APA
Bollt, E., Fish, J., Kumar, A., Santos, E. S. dos, & Laurienti, P. J. (2023). Fractal basins as a mechanism for the nimble brain. Scientific Reports, 13, 1-11. doi:10.1038/s41598-023-45664-5
NLM
Bollt E, Fish J, Kumar A, Santos ES dos, Laurienti PJ. Fractal basins as a mechanism for the nimble brain [Internet]. Scientific Reports. 2023 ; 13 1-11.[citado 2024 set. 04 ] Available from: https://doi.org/10.1038/s41598-023-45664-5
Vancouver
Bollt E, Fish J, Kumar A, Santos ES dos, Laurienti PJ. Fractal basins as a mechanism for the nimble brain [Internet]. Scientific Reports. 2023 ; 13 1-11.[citado 2024 set. 04 ] Available from: https://doi.org/10.1038/s41598-023-45664-5
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SPADON, Gabriel et al. Pay attention to evolution: time series forecasting with deep graph-evolution learning. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM, v. 44, n. 9, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.1109/TPAMI.2021.3076155. Acesso em: 04 set. 2024.
APA
Spadon, G., Hong, S., Machado, B. B., Matwin, S., Rodrigues Junior, J. F., & Sun, J. (2022). Pay attention to evolution: time series forecasting with deep graph-evolution learning. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM, 44( 9), Se 2022. doi:10.1109/TPAMI.2021.3076155
NLM
Spadon G, Hong S, Machado BB, Matwin S, Rodrigues Junior JF, Sun J. Pay attention to evolution: time series forecasting with deep graph-evolution learning [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. 2022 ; 44( 9): Se 2022.[citado 2024 set. 04 ] Available from: https://doi.org/10.1109/TPAMI.2021.3076155
Vancouver
Spadon G, Hong S, Machado BB, Matwin S, Rodrigues Junior JF, Sun J. Pay attention to evolution: time series forecasting with deep graph-evolution learning [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. 2022 ; 44( 9): Se 2022.[citado 2024 set. 04 ] Available from: https://doi.org/10.1109/TPAMI.2021.3076155
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RAMOS, Eduardo e NOLASCO, Victor Hugo e GAMEIRO, Márcio Fuzeto. Rigorous enclosures of solutions of Neumann boundary value problems. Applied Numerical Mathematics, v. 180, p. 104-119, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.apnum.2022.05.011. Acesso em: 04 set. 2024.
APA
Ramos, E., Nolasco, V. H., & Gameiro, M. F. (2022). Rigorous enclosures of solutions of Neumann boundary value problems. Applied Numerical Mathematics, 180, 104-119. doi:10.1016/j.apnum.2022.05.011
NLM
Ramos E, Nolasco VH, Gameiro MF. Rigorous enclosures of solutions of Neumann boundary value problems [Internet]. Applied Numerical Mathematics. 2022 ; 180 104-119.[citado 2024 set. 04 ] Available from: https://doi.org/10.1016/j.apnum.2022.05.011
Vancouver
Ramos E, Nolasco VH, Gameiro MF. Rigorous enclosures of solutions of Neumann boundary value problems [Internet]. Applied Numerical Mathematics. 2022 ; 180 104-119.[citado 2024 set. 04 ] Available from: https://doi.org/10.1016/j.apnum.2022.05.011
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CASTELO, Antonio e BUENO, Lucas Moutinho e GAMEIRO, Márcio Fuzeto. A combinatorial marching hypercubes algorithm. Computers and Graphics, v. 102, p. 67-77, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.cag.2021.10.023. Acesso em: 04 set. 2024.
APA
Castelo, A., Bueno, L. M., & Gameiro, M. F. (2022). A combinatorial marching hypercubes algorithm. Computers and Graphics, 102, 67-77. doi:10.1016/j.cag.2021.10.023
NLM
Castelo A, Bueno LM, Gameiro MF. A combinatorial marching hypercubes algorithm [Internet]. Computers and Graphics. 2022 ; 102 67-77.[citado 2024 set. 04 ] Available from: https://doi.org/10.1016/j.cag.2021.10.023
Vancouver
Castelo A, Bueno LM, Gameiro MF. A combinatorial marching hypercubes algorithm [Internet]. Computers and Graphics. 2022 ; 102 67-77.[citado 2024 set. 04 ] Available from: https://doi.org/10.1016/j.cag.2021.10.023
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CUMMINS, Breschine et al. Experimental guidance for discovering genetic networks through hypothesis reduction on time series. PLoS Computational Biology, v. 18, n. 10, p. 1-31, 2022Tradução . . Disponível em: https://doi.org/10.1371/journal.pcbi.1010145. Acesso em: 04 set. 2024.
APA
Cummins, B., Motta, F. C., Moseley, R. C., Deckard, A., Campione, S., Gameiro, M. F., et al. (2022). Experimental guidance for discovering genetic networks through hypothesis reduction on time series. PLoS Computational Biology, 18( 10), 1-31. doi:10.1371/journal.pcbi.1010145
NLM
Cummins B, Motta FC, Moseley RC, Deckard A, Campione S, Gameiro MF, Gedeon T, Mischaikow K, Haase S. Experimental guidance for discovering genetic networks through hypothesis reduction on time series [Internet]. PLoS Computational Biology. 2022 ; 18( 10): 1-31.[citado 2024 set. 04 ] Available from: https://doi.org/10.1371/journal.pcbi.1010145
Vancouver
Cummins B, Motta FC, Moseley RC, Deckard A, Campione S, Gameiro MF, Gedeon T, Mischaikow K, Haase S. Experimental guidance for discovering genetic networks through hypothesis reduction on time series [Internet]. PLoS Computational Biology. 2022 ; 18( 10): 1-31.[citado 2024 set. 04 ] Available from: https://doi.org/10.1371/journal.pcbi.1010145
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MORETTI, Caio Benatti et al. Robotic kinematic measures of the arm in chronic Stroke: part 1 – motor recovery patterns from tDCS preceding intensive training. Bioelectronic Medicine, v. 7, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1186/s42234-021-00082-8. Acesso em: 04 set. 2024.
APA
Moretti, C. B., Edwards, D. J., Hamilton, T., Cortes, M., Peltz, A. R., Chang, J. L., et al. (2021). Robotic kinematic measures of the arm in chronic Stroke: part 1 – motor recovery patterns from tDCS preceding intensive training. Bioelectronic Medicine, 7, 1-13. doi:10.1186/s42234-021-00082-8
NLM
Moretti CB, Edwards DJ, Hamilton T, Cortes M, Peltz AR, Chang JL, Delbem ACB, Volpe BT, Krebs HI. Robotic kinematic measures of the arm in chronic Stroke: part 1 – motor recovery patterns from tDCS preceding intensive training [Internet]. Bioelectronic Medicine. 2021 ; 7 1-13.[citado 2024 set. 04 ] Available from: https://doi.org/10.1186/s42234-021-00082-8
Vancouver
Moretti CB, Edwards DJ, Hamilton T, Cortes M, Peltz AR, Chang JL, Delbem ACB, Volpe BT, Krebs HI. Robotic kinematic measures of the arm in chronic Stroke: part 1 – motor recovery patterns from tDCS preceding intensive training [Internet]. Bioelectronic Medicine. 2021 ; 7 1-13.[citado 2024 set. 04 ] Available from: https://doi.org/10.1186/s42234-021-00082-8
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MORETTI, Caio Benatti et al. Robotic kinematic measures of the arm in chronic Stroke: part 2 – strong correlation with clinical outcome measures. Bioelectronic Medicine, v. 7, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1186/s42234-021-00082-8. Acesso em: 04 set. 2024.
APA
Moretti, C. B., Hamilton, T., Edwards, D. J., Peltz, A. R., Chang, J. L., Cortes, M., et al. (2021). Robotic kinematic measures of the arm in chronic Stroke: part 2 – strong correlation with clinical outcome measures. Bioelectronic Medicine, 7, 1-13. doi:10.1186/s42234-021-00082-8
NLM
Moretti CB, Hamilton T, Edwards DJ, Peltz AR, Chang JL, Cortes M, Delbem ACB, Volpe BT, Krebs HI. Robotic kinematic measures of the arm in chronic Stroke: part 2 – strong correlation with clinical outcome measures [Internet]. Bioelectronic Medicine. 2021 ; 7 1-13.[citado 2024 set. 04 ] Available from: https://doi.org/10.1186/s42234-021-00082-8
Vancouver
Moretti CB, Hamilton T, Edwards DJ, Peltz AR, Chang JL, Cortes M, Delbem ACB, Volpe BT, Krebs HI. Robotic kinematic measures of the arm in chronic Stroke: part 2 – strong correlation with clinical outcome measures [Internet]. Bioelectronic Medicine. 2021 ; 7 1-13.[citado 2024 set. 04 ] Available from: https://doi.org/10.1186/s42234-021-00082-8