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Filtros : "MODELOS PARA PROCESSOS ESTOCÁSTICOS" "Financiado pelo CNPq" Limpar

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1 - 11 (11 records)

  • Artigo de periodico

    Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data (2021)

    Hernández, Noslen ; Duarte, Aline ; Ost, Guilherme ; Fraiman, Ricardo ; Galves, Antonio ; Vargas, Claudia D.

    Source: Scientific Reports. Unidade: IME

    Assunto: MODELOS PARA PROCESSOS ESTOCÁSTICOS

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    • ABNT

      HERNÁNDEZ, Noslen et al. Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data. Scientific Reports, v. 11, n. art. 3520, p. 1-15, 2021Tradução . . Disponível em: https://doi.org/10.1038/s41598-021-83119-x. Acesso em: 10 nov. 2025.

    • APA

      Hernández, N., Duarte, A., Ost, G., Fraiman, R., Galves, A., & Vargas, C. D. (2021). Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data. Scientific Reports, 11( art. 3520), 1-15. doi:10.1038/s41598-021-83119-x

    • NLM

      Hernández N, Duarte A, Ost G, Fraiman R, Galves A, Vargas CD. Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data [Internet]. Scientific Reports. 2021 ; 11( art. 3520): 1-15.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1038/s41598-021-83119-x

    • Vancouver

      Hernández N, Duarte A, Ost G, Fraiman R, Galves A, Vargas CD. Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data [Internet]. Scientific Reports. 2021 ; 11( art. 3520): 1-15.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1038/s41598-021-83119-x

  • Trabalho de evento-resumo periodico

    Efficient predictive uncertainty estimators for deep probabilistic models (2020)

    Llerena, Julissa Villanueva ; Mauá, Denis Deratani

    Source: Proceddings : AAAI-20 Student Tracks. Conference titles: AAAI Conference on Artificial Intelligence - AAAI. Unidade: IME

    Assunto: MODELOS PARA PROCESSOS ESTOCÁSTICOS

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    • ABNT

      LLERENA, Julissa Villanueva e MAUÁ, Denis Deratani. Efficient predictive uncertainty estimators for deep probabilistic models. Proceddings : AAAI-20 Student Tracks. Palo Alto: AAAI Press. Disponível em: https://doi.org/10.1609/aaai.v34i10.7142. Acesso em: 10 nov. 2025. , 2020

    • APA

      Llerena, J. V., & Mauá, D. D. (2020). Efficient predictive uncertainty estimators for deep probabilistic models. Proceddings : AAAI-20 Student Tracks. Palo Alto: AAAI Press. doi:10.1609/aaai.v34i10.7142

    • NLM

      Llerena JV, Mauá DD. Efficient predictive uncertainty estimators for deep probabilistic models [Internet]. Proceddings : AAAI-20 Student Tracks. 2020 ; 35( 100): 13740-13741.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1609/aaai.v34i10.7142

    • Vancouver

      Llerena JV, Mauá DD. Efficient predictive uncertainty estimators for deep probabilistic models [Internet]. Proceddings : AAAI-20 Student Tracks. 2020 ; 35( 100): 13740-13741.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1609/aaai.v34i10.7142

  • Trabalho de evento

    Finding feasible policies for extreme risk-averse agents in probabilistic planning (2020)

    Fernandez, Milton Condori; Barros, Leliane Nunes de ; Mauá, Denis Deratani ; Delgado, Karina Valdivia ; Silva, Valdinei Freire da

    Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: IME, EACH

    Subjects: PROBABILIDADE, MODELOS PARA PROCESSOS ESTOCÁSTICOS, ANÁLISE DE RISCO

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    • ABNT

      FERNANDEZ, Milton Condori et al. Finding feasible policies for extreme risk-averse agents in probabilistic planning. 2020, Anais.. Cham: Springer, 2020. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_7. Acesso em: 10 nov. 2025.

    • APA

      Fernandez, M. C., Barros, L. N. de, Mauá, D. D., Delgado, K. V., & Silva, V. F. da. (2020). Finding feasible policies for extreme risk-averse agents in probabilistic planning. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-61380-8_7

    • NLM

      Fernandez MC, Barros LN de, Mauá DD, Delgado KV, Silva VF da. Finding feasible policies for extreme risk-averse agents in probabilistic planning [Internet]. Proceedings. 2020 ;[citado 2025 nov. 10 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_7

    • Vancouver

      Fernandez MC, Barros LN de, Mauá DD, Delgado KV, Silva VF da. Finding feasible policies for extreme risk-averse agents in probabilistic planning [Internet]. Proceedings. 2020 ;[citado 2025 nov. 10 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_7

  • Artigo de periodico

    Thirty years of credal networks: specification, algorithms and complexity (2020)

    Mauá, Denis Deratani ; Cozman, Fabio Gagliardi

    Source: International Journal of Approximate Reasoning. Unidades: IME, EP

    Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS, PROBABILIDADE

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    • ABNT

      MAUÁ, Denis Deratani e COZMAN, Fabio Gagliardi. Thirty years of credal networks: specification, algorithms and complexity. International Journal of Approximate Reasoning, v. 126, p. 133-157, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2020.08.009. Acesso em: 10 nov. 2025.

    • APA

      Mauá, D. D., & Cozman, F. G. (2020). Thirty years of credal networks: specification, algorithms and complexity. International Journal of Approximate Reasoning, 126, 133-157. doi:10.1016/j.ijar.2020.08.009

    • NLM

      Mauá DD, Cozman FG. Thirty years of credal networks: specification, algorithms and complexity [Internet]. International Journal of Approximate Reasoning. 2020 ; 126 133-157.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.ijar.2020.08.009

    • Vancouver

      Mauá DD, Cozman FG. Thirty years of credal networks: specification, algorithms and complexity [Internet]. International Journal of Approximate Reasoning. 2020 ; 126 133-157.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.ijar.2020.08.009

  • Artigo de periodico

    Efficient algorithms for robustness analysis of maximum a posteriori inference in selective sum-product networks (2020)

    Villanueva Llerena, Julissa ; Mauá, Denis Deratani

    Source: International Journal of Approximate Reasoning. Unidade: IME

    Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS, APRENDIZADO COMPUTACIONAL

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    • ABNT

      VILLANUEVA LLERENA, Julissa e MAUÁ, Denis Deratani. Efficient algorithms for robustness analysis of maximum a posteriori inference in selective sum-product networks. International Journal of Approximate Reasoning, v. 126, p. 158-180-, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2020.07.008. Acesso em: 10 nov. 2025.

    • APA

      Villanueva Llerena, J., & Mauá, D. D. (2020). Efficient algorithms for robustness analysis of maximum a posteriori inference in selective sum-product networks. International Journal of Approximate Reasoning, 126, 158-180-. doi:10.1016/j.ijar.2020.07.008

    • NLM

      Villanueva Llerena J, Mauá DD. Efficient algorithms for robustness analysis of maximum a posteriori inference in selective sum-product networks [Internet]. International Journal of Approximate Reasoning. 2020 ; 126 158-180-.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.ijar.2020.07.008

    • Vancouver

      Villanueva Llerena J, Mauá DD. Efficient algorithms for robustness analysis of maximum a posteriori inference in selective sum-product networks [Internet]. International Journal of Approximate Reasoning. 2020 ; 126 158-180-.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.ijar.2020.07.008

  • Artigo de periodico

    Estimating the interaction graph of stochastic neural dynamics (2019)

    Duarte, Aline ; Galves, Antonio ; Löcherbach, Eva ; Ost, Guilherme

    Source: Bernoulli. Unidade: IME

    Subjects: BIOESTATÍSTICA, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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    • ABNT

      DUARTE, Aline et al. Estimating the interaction graph of stochastic neural dynamics. Bernoulli, v. 25, n. 1, p. 771-792, 2019Tradução . . Disponível em: https://doi.org/10.3150/17-bej1006. Acesso em: 10 nov. 2025.

    • APA

      Duarte, A., Galves, A., Löcherbach, E., & Ost, G. (2019). Estimating the interaction graph of stochastic neural dynamics. Bernoulli, 25( 1), 771-792. doi:10.3150/17-bej1006

    • NLM

      Duarte A, Galves A, Löcherbach E, Ost G. Estimating the interaction graph of stochastic neural dynamics [Internet]. Bernoulli. 2019 ; 25( 1): 771-792.[citado 2025 nov. 10 ] Available from: https://doi.org/10.3150/17-bej1006

    • Vancouver

      Duarte A, Galves A, Löcherbach E, Ost G. Estimating the interaction graph of stochastic neural dynamics [Internet]. Bernoulli. 2019 ; 25( 1): 771-792.[citado 2025 nov. 10 ] Available from: https://doi.org/10.3150/17-bej1006

  • Artigo de periodico

    RNA polymerase interactions and elongation rate (2019)

    Belitsky, Vladimir ; Schutz, G. M

    Source: Journal of Theoretical Biology. Unidade: IME

    Subjects: RNA POLIMERASES, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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      BELITSKY, Vladimir e SCHUTZ, G. M. RNA polymerase interactions and elongation rate. Journal of Theoretical Biology, v. 462, p. 370-380, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.jtbi.2018.11.025. Acesso em: 10 nov. 2025.

    • APA

      Belitsky, V., & Schutz, G. M. (2019). RNA polymerase interactions and elongation rate. Journal of Theoretical Biology, 462, 370-380. doi:10.1016/j.jtbi.2018.11.025

    • NLM

      Belitsky V, Schutz GM. RNA polymerase interactions and elongation rate [Internet]. Journal of Theoretical Biology. 2019 ; 462 370-380.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.jtbi.2018.11.025

    • Vancouver

      Belitsky V, Schutz GM. RNA polymerase interactions and elongation rate [Internet]. Journal of Theoretical Biology. 2019 ; 462 370-380.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.jtbi.2018.11.025

  • Artigo de periodico

    Stochastic estimation of potential and depleted productivity of soybean grain and oil (2019)

    Alambert, Marcelo Rodrigues; Umburanas, Renan Caldas; Schwerz, Felipe; Reichardt, Klaus; Dourado-Neto, Durval

    Source: International Journal of Plant Production. Unidade: ESALQ

    Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS, ÓLEO DE SOJA, SOJA

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      ALAMBERT, Marcelo Rodrigues et al. Stochastic estimation of potential and depleted productivity of soybean grain and oil. International Journal of Plant Production, p. 1-14, 2019Tradução . . Disponível em: https://doi.org/10.1007/s42106-019-00042-y. Acesso em: 10 nov. 2025.

    • APA

      Alambert, M. R., Umburanas, R. C., Schwerz, F., Reichardt, K., & Dourado-Neto, D. (2019). Stochastic estimation of potential and depleted productivity of soybean grain and oil. International Journal of Plant Production, 1-14. doi:10.1007/s42106-019-00042-y

    • NLM

      Alambert MR, Umburanas RC, Schwerz F, Reichardt K, Dourado-Neto D. Stochastic estimation of potential and depleted productivity of soybean grain and oil [Internet]. International Journal of Plant Production. 2019 ; 1-14.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1007/s42106-019-00042-y

    • Vancouver

      Alambert MR, Umburanas RC, Schwerz F, Reichardt K, Dourado-Neto D. Stochastic estimation of potential and depleted productivity of soybean grain and oil [Internet]. International Journal of Plant Production. 2019 ; 1-14.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1007/s42106-019-00042-y

  • Artigo de periodico

    Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks (2018)

    Pena, Rodrigo Felipe de Oliveira; Vellmer, Sebastian; Bernardi, Davide; Roque, Antônio Carlos; Lindner, Benjamin

    Source: Frontiers in Computational Neuroscience. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDE NERVOSA, REDES NEURAIS, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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    • ABNT

      PENA, Rodrigo Felipe de Oliveira et al. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks. Frontiers in Computational Neuroscience, v. 12, 2018Tradução . . Disponível em: https://doi.org/10.3389/fncom.2018.00009. Acesso em: 10 nov. 2025.

    • APA

      Pena, R. F. de O., Vellmer, S., Bernardi, D., Roque, A. C., & Lindner, B. (2018). Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks. Frontiers in Computational Neuroscience, 12. doi:10.3389/fncom.2018.00009

    • NLM

      Pena RF de O, Vellmer S, Bernardi D, Roque AC, Lindner B. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks [Internet]. Frontiers in Computational Neuroscience. 2018 ; 12[citado 2025 nov. 10 ] Available from: https://doi.org/10.3389/fncom.2018.00009

    • Vancouver

      Pena RF de O, Vellmer S, Bernardi D, Roque AC, Lindner B. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks [Internet]. Frontiers in Computational Neuroscience. 2018 ; 12[citado 2025 nov. 10 ] Available from: https://doi.org/10.3389/fncom.2018.00009

  • Artigo de periodico

    Robustifying sum-product networks (2018)

    Mauá, Denis Deratani ; Conaty, Diarmaid; Cozman, Fabio Gagliardi ; Poppenhaeger, Katja; Campos, Cassio Polpo de

    Source: International Journal of Approximate Reasoning. Unidades: IME, EP

    Subjects: INTELIGÊNCIA ARTIFICIAL, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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    • ABNT

      MAUÁ, Denis Deratani et al. Robustifying sum-product networks. International Journal of Approximate Reasoning, v. 101, p. 163-180, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2018.07.003. Acesso em: 10 nov. 2025.

    • APA

      Mauá, D. D., Conaty, D., Cozman, F. G., Poppenhaeger, K., & Campos, C. P. de. (2018). Robustifying sum-product networks. International Journal of Approximate Reasoning, 101, 163-180. doi:10.1016/j.ijar.2018.07.003

    • NLM

      Mauá DD, Conaty D, Cozman FG, Poppenhaeger K, Campos CP de. Robustifying sum-product networks [Internet]. International Journal of Approximate Reasoning. 2018 ; 101 163-180.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.ijar.2018.07.003

    • Vancouver

      Mauá DD, Conaty D, Cozman FG, Poppenhaeger K, Campos CP de. Robustifying sum-product networks [Internet]. International Journal of Approximate Reasoning. 2018 ; 101 163-180.[citado 2025 nov. 10 ] Available from: https://doi.org/10.1016/j.ijar.2018.07.003

  • Trabalho de evento-anais periodico

    Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming (2017)

    Bueno, Thiago Pereira; Mauá, Denis Deratani ; Barros, Leliane Nunes de ; Cozman, Fabio Gagliardi

    Source: PMLR: Proceedings of Machine Learning Research. Conference titles: International Symposium on Imprecise Probability: Theories and Applications - ISIPTA. Unidades: IME, EP

    Subjects: PROCESSOS DE MARKOV, PROGRAMAÇÃO LÓGICA, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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      BUENO, Thiago Pereira et al. Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming. PMLR: Proceedings of Machine Learning Research. Brookline: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: http://proceedings.mlr.press/v62/bueno17a.html. Acesso em: 10 nov. 2025. , 2017

    • APA

      Bueno, T. P., Mauá, D. D., Barros, L. N. de, & Cozman, F. G. (2017). Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming. PMLR: Proceedings of Machine Learning Research. Brookline: Instituto de Matemática e Estatística, Universidade de São Paulo. Recuperado de http://proceedings.mlr.press/v62/bueno17a.html

    • NLM

      Bueno TP, Mauá DD, Barros LN de, Cozman FG. Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming [Internet]. PMLR: Proceedings of Machine Learning Research. 2017 ;( 62): 49-60.[citado 2025 nov. 10 ] Available from: http://proceedings.mlr.press/v62/bueno17a.html

    • Vancouver

      Bueno TP, Mauá DD, Barros LN de, Cozman FG. Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming [Internet]. PMLR: Proceedings of Machine Learning Research. 2017 ;( 62): 49-60.[citado 2025 nov. 10 ] Available from: http://proceedings.mlr.press/v62/bueno17a.html
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