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Trabalho de evento
Quantifying uncertainty in bayesian networks structural learning (2024)
Barth, Vitor Bruno de Oliveira; Caetano, Henrique de Oliveira; Maciel, Carlos Dias ; Aiello, Marco
Source: Proceedings. Conference titles: IEEE International Conference on Evolving and Adaptive Intelligent Systems. Unidade: EESC
Subjects: INFERÊNCIA BAYESIANA, APRENDIZADO COMPUTACIONAL, ENGENHARIA ELÉTRICA
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ABNT
BARTH, Vitor Bruno de Oliveira et al. Quantifying uncertainty in bayesian networks structural learning. 2024, Anais.. Picataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2024. Disponível em: https://dx.doi.org/10.1109/EAIS58494.2024.10570017. Acesso em: 22 dez. 2024.
APA
Barth, V. B. de O., Caetano, H. de O., Maciel, C. D., & Aiello, M. (2024). Quantifying uncertainty in bayesian networks structural learning. In Proceedings. Picataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1109/EAIS58494.2024.10570017
NLM
Barth VB de O, Caetano H de O, Maciel CD, Aiello M. Quantifying uncertainty in bayesian networks structural learning [Internet]. Proceedings. 2024 ;[citado 2024 dez. 22 ] Available from: https://dx.doi.org/10.1109/EAIS58494.2024.10570017
Vancouver
Barth VB de O, Caetano H de O, Maciel CD, Aiello M. Quantifying uncertainty in bayesian networks structural learning [Internet]. Proceedings. 2024 ;[citado 2024 dez. 22 ] Available from: https://dx.doi.org/10.1109/EAIS58494.2024.10570017
Artigo de periodico
Multiclass classification of autism spectrum disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis (2024)
Alves, Caroline Lourenço ; Martinelli, Tiago; Sallum, Loriz Francisco ; Rodrigues, Francisco Aparecido ; Toutain, Thaise Graziele Lima de ; Porto, Joel Augusto Moura ; Thielemann, Christiane ; Aguiar, Patricia Maria de Carvalho ; Moeckel, Michael
Source: PLoS One. Unidades: ICMC, IFSC, INTER: ICMC -UFSCAR
Subjects: APRENDIZADO COMPUTACIONAL, RESSONÂNCIA MAGNÉTICA, BENCHMARKS, TRANSTORNO DO DEFICIT DE ATENÇÃO COM HIPERATIVIDADE, TRANSTORNO DO ESPECTRO AUTISTA
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ABNT
ALVES, Caroline Lourenço et al. Multiclass classification of autism spectrum disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis. PLoS One, v. 19, n. 10, p. 1-35, 2024Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0305630. Acesso em: 22 dez. 2024.
APA
Alves, C. L., Martinelli, T., Sallum, L. F., Rodrigues, F. A., Toutain, T. G. L. de, Porto, J. A. M., et al. (2024). Multiclass classification of autism spectrum disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis. PLoS One, 19( 10), 1-35. doi:10.1371/journal.pone.0305630
NLM
Alves CL, Martinelli T, Sallum LF, Rodrigues FA, Toutain TGL de, Porto JAM, Thielemann C, Aguiar PM de C, Moeckel M. Multiclass classification of autism spectrum disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis [Internet]. PLoS One. 2024 ; 19( 10): 1-35.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1371/journal.pone.0305630
Vancouver
Alves CL, Martinelli T, Sallum LF, Rodrigues FA, Toutain TGL de, Porto JAM, Thielemann C, Aguiar PM de C, Moeckel M. Multiclass classification of autism spectrum disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis [Internet]. PLoS One. 2024 ; 19( 10): 1-35.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1371/journal.pone.0305630
Artigo de periodico
An evaluation of iron ore characteristics through machine learning and 2-D LiDAR technology (2024)
Matos, Saulo Neves ; Pinto, Thomas V. B. e ; Domingues, Jacó Dias ; Ranieri, Caetano Mazzoni ; Albuquerque, Kaike S ; Moreira, Vinicius da Silva ; Souza, Ernandes Sávio ; Ueyama, Jó ; Euzébio, Thiago A. M ; Pessin, Gustavo
Source: IEEE Transactions on Instrumentation and Measurement. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, INDÚSTRIA MINERAL, ESTATÍSTICA, MINERAÇÃO
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ABNT
MATOS, Saulo Neves et al. An evaluation of iron ore characteristics through machine learning and 2-D LiDAR technology. IEEE Transactions on Instrumentation and Measurement, v. 73, p. 1-11, 2024Tradução . . Disponível em: https://doi.org/10.1109/TIM.2023.3342220. Acesso em: 22 dez. 2024.
APA
Matos, S. N., Pinto, T. V. B. e, Domingues, J. D., Ranieri, C. M., Albuquerque, K. S., Moreira, V. da S., et al. (2024). An evaluation of iron ore characteristics through machine learning and 2-D LiDAR technology. IEEE Transactions on Instrumentation and Measurement, 73, 1-11. doi:10.1109/TIM.2023.3342220
NLM
Matos SN, Pinto TVB e, Domingues JD, Ranieri CM, Albuquerque KS, Moreira V da S, Souza ES, Ueyama J, Euzébio TAM, Pessin G. An evaluation of iron ore characteristics through machine learning and 2-D LiDAR technology [Internet]. IEEE Transactions on Instrumentation and Measurement. 2024 ; 73 1-11.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/TIM.2023.3342220
Vancouver
Matos SN, Pinto TVB e, Domingues JD, Ranieri CM, Albuquerque KS, Moreira V da S, Souza ES, Ueyama J, Euzébio TAM, Pessin G. An evaluation of iron ore characteristics through machine learning and 2-D LiDAR technology [Internet]. IEEE Transactions on Instrumentation and Measurement. 2024 ; 73 1-11.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/TIM.2023.3342220
Trabalho de evento
NatUKE: a benchmark for natural product knowledge extraction from academic literature (2023)
Carmo, Paulo Viviurka do ; Marx, Edgard ; Marcacini, Ricardo Marcondes ; Valli, Marilia ; Silva-Silva, João Victor ; Pilon, Alan
Source: Proceedings. Conference titles: IEEE International Conference on Semantic Computing - ICSC. Unidades: ICMC, IFSC, FCFRP
Subjects: DESCOBERTA DE CONHECIMENTO, MINERAÇÃO DE DADOS, APRENDIZADO COMPUTACIONAL, BENCHMARKS, PRODUTOS NATURAIS
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ABNT
CARMO, Paulo Viviurka do et al. NatUKE: a benchmark for natural product knowledge extraction from academic literature. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/ICSC56153.2023.00039. Acesso em: 22 dez. 2024.
APA
Carmo, P. V. do, Marx, E., Marcacini, R. M., Valli, M., Silva-Silva, J. V., & Pilon, A. (2023). NatUKE: a benchmark for natural product knowledge extraction from academic literature. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICSC56153.2023.00039
NLM
Carmo PV do, Marx E, Marcacini RM, Valli M, Silva-Silva JV, Pilon A. NatUKE: a benchmark for natural product knowledge extraction from academic literature [Internet]. Proceedings. 2023 ;[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/ICSC56153.2023.00039
Vancouver
Carmo PV do, Marx E, Marcacini RM, Valli M, Silva-Silva JV, Pilon A. NatUKE: a benchmark for natural product knowledge extraction from academic literature [Internet]. Proceedings. 2023 ;[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/ICSC56153.2023.00039
Artigo de periodico
Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments (2022)
Alves, Caroline Lourenço ; Cury, Rubens Gisbert ; Roster, Kirstin ; Pineda, Aruane Mello ; Rodrigues, Francisco Aparecido ; Thielemann, Christiane ; Ciba, Manuel
Source: PLoS ONE. Unidades: ICMC, FM
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, ELETROENCEFALOGRAFIA
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ABNT
ALVES, Caroline Lourenço et al. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLoS ONE, v. 17, n. 12, p. 1-26, 2022Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0277257. Acesso em: 22 dez. 2024.
APA
Alves, C. L., Cury, R. G., Roster, K., Pineda, A. M., Rodrigues, F. A., Thielemann, C., & Ciba, M. (2022). Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLoS ONE, 17( 12), 1-26. doi:10.1371/journal.pone.0277257
NLM
Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments [Internet]. PLoS ONE. 2022 ; 17( 12): 1-26.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1371/journal.pone.0277257
Vancouver
Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments [Internet]. PLoS ONE. 2022 ; 17( 12): 1-26.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1371/journal.pone.0277257
Trabalho de evento-anais periodico
YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone (2022)
Casanova, Edresson ; Weber, Julian; Shulby, Christopher Dane ; Candido Junior, Arnaldo ; Gölge, Eren; Ponti, Moacir Antonelli
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: International Conference on Machine Learning - ICML. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DA FALA, SÍNTESE DE FALA
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ABNT
CASANOVA, Edresson et al. YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v162/casanova22a.html. Acesso em: 22 dez. 2024. , 2022
APA
Casanova, E., Weber, J., Shulby, C. D., Candido Junior, A., Gölge, E., & Ponti, M. A. (2022). YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v162/casanova22a.html
NLM
Casanova E, Weber J, Shulby CD, Candido Junior A, Gölge E, Ponti MA. YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 162 2709-2720.[citado 2024 dez. 22 ] Available from: https://proceedings.mlr.press/v162/casanova22a.html
Vancouver
Casanova E, Weber J, Shulby CD, Candido Junior A, Gölge E, Ponti MA. YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 162 2709-2720.[citado 2024 dez. 22 ] Available from: https://proceedings.mlr.press/v162/casanova22a.html
Artigo de periodico-carta/editorial
The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] (2022)
Soares, Thereza A. ; Alves, Ariane Ferreira Nunes; Mazzolari, Angelica; Ruggiu, Fiorella; Wei, Guo-Wei; Merz, Kenneth
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: APRENDIZADO COMPUTACIONAL, MODELOS MATEMÁTICOS, ESTRUTURA MOLECULAR (QUÍMICA TEÓRICA)
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ABNT
SOARES, Thereza A. et al. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1021/acs.jcim.2c01422. Acesso em: 22 dez. 2024. , 2022
APA
Soares, T. A., Alves, A. F. N., Mazzolari, A., Ruggiu, F., Wei, G. -W., & Merz, K. (2022). The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1021/acs.jcim.2c01422
NLM
Soares TA, Alves AFN, Mazzolari A, Ruggiu F, Wei G-W, Merz K. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 22): 5317-5320.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422
Vancouver
Soares TA, Alves AFN, Mazzolari A, Ruggiu F, Wei G-W, Merz K. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 22): 5317-5320.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422
Trabalho de evento
Can deep models benefit from standard preprocessing of pulsed thermography data? (2022)
Wei, Z.; Osman, A.; Muller, D.; Fernandes, H.; Tarpani, José Ricardo ; Maldague, X.
Conference titles: International Conference on Infrared, Millimeter and Terahertz Waves - IRMMW-THz. Unidade: EESC
Subjects: TERMOGRAFIA, APRENDIZADO COMPUTACIONAL, MATERIAIS
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ABNT
WEI, Z. et al. Can deep models benefit from standard preprocessing of pulsed thermography data? 2022, Anais.. Piscataway, NJ, USA: IEEE, 2022. Disponível em: https://doi.org/10.1109/IRMMW-THz50927.2022.9896112. Acesso em: 22 dez. 2024.
APA
Wei, Z., Osman, A., Muller, D., Fernandes, H., Tarpani, J. R., & Maldague, X. (2022). Can deep models benefit from standard preprocessing of pulsed thermography data? In . Piscataway, NJ, USA: IEEE. doi:10.1109/IRMMW-THz50927.2022.9896112
NLM
Wei Z, Osman A, Muller D, Fernandes H, Tarpani JR, Maldague X. Can deep models benefit from standard preprocessing of pulsed thermography data? [Internet]. 2022 ;[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/IRMMW-THz50927.2022.9896112
Vancouver
Wei Z, Osman A, Muller D, Fernandes H, Tarpani JR, Maldague X. Can deep models benefit from standard preprocessing of pulsed thermography data? [Internet]. 2022 ;[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/IRMMW-THz50927.2022.9896112
Artigo de periodico
A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell (2022)
Segura, Mayra Luisa Ruiz Tejada ; Moussa, Eman Abou; Garabello, Elisa; Nakahara, Thiago Seike Picoreti ; Makhlouf, Melanie ; Mathew, Lisa S ; Wang, Li; Valle, Filippo ; Huang, Susie S. Y; Mainland, Joel D ; Caselle, Michele ; Osella, Matteo ; Lorenz, Stephan ; Reisert, Johannes; Logan, Darren W ; Malnic, Bettina ; Scialdone, Antonio ; Saraiva, Luis R
Source: Cell Reports. Unidade: IQ
Subjects: MUCOSA RESPIRATÓRIA, OLFATO, EPITÉLIO, APRENDIZADO COMPUTACIONAL
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ABNT
SEGURA, Mayra Luisa Ruiz Tejada et al. A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell. Cell Reports, v. 38 , p. 1-23 art. 110547, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.celrep.2022.110547. Acesso em: 22 dez. 2024.
APA
Segura, M. L. R. T., Moussa, E. A., Garabello, E., Nakahara, T. S. P., Makhlouf, M., Mathew, L. S., et al. (2022). A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell. Cell Reports, 38 , 1-23 art. 110547. doi:10.1016/j.celrep.2022.110547
NLM
Segura MLRT, Moussa EA, Garabello E, Nakahara TSP, Makhlouf M, Mathew LS, Wang L, Valle F, Huang SSY, Mainland JD, Caselle M, Osella M, Lorenz S, Reisert J, Logan DW, Malnic B, Scialdone A, Saraiva LR. A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell [Internet]. Cell Reports. 2022 ;38 1-23 art. 110547.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1016/j.celrep.2022.110547
Vancouver
Segura MLRT, Moussa EA, Garabello E, Nakahara TSP, Makhlouf M, Mathew LS, Wang L, Valle F, Huang SSY, Mainland JD, Caselle M, Osella M, Lorenz S, Reisert J, Logan DW, Malnic B, Scialdone A, Saraiva LR. A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell [Internet]. Cell Reports. 2022 ;38 1-23 art. 110547.[citado 2024 dez. 22 ] Available from: https://doi.org/10.1016/j.celrep.2022.110547
Trabalho de evento
Reducing the need for bounding box annotations in object detection using image classification data (2021)
Blanger, Leonardo ; Hirata, Nina Sumiko Tomita ; Jiang, Xiaoyi
Source: Proceedings. Conference titles: Brazilian Symposium on Computer Graphics and Image Processing - SIBGRAPI. Unidade: IME
Subjects: VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE OBJETOS
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ABNT
BLANGER, Leonardo e HIRATA, Nina Sumiko Tomita e JIANG, Xiaoyi. Reducing the need for bounding box annotations in object detection using image classification data. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00035. Acesso em: 22 dez. 2024.
APA
Blanger, L., Hirata, N. S. T., & Jiang, X. (2021). Reducing the need for bounding box annotations in object detection using image classification data. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI54419.2021.00035
NLM
Blanger L, Hirata NST, Jiang X. Reducing the need for bounding box annotations in object detection using image classification data [Internet]. Proceedings. 2021 ;[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00035
Vancouver
Blanger L, Hirata NST, Jiang X. Reducing the need for bounding box annotations in object detection using image classification data [Internet]. Proceedings. 2021 ;[citado 2024 dez. 22 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00035
Artigo de periodico
OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes (2021)
Saraiva, João Pedro ; Bartholomäus, Alexander ; Kallies, René ; Gomes, Marta; Bicalho, Marcos; Kasmanas, Jonas Coelho ; Vogt, Carsten ; Chatzinotas, Antonis ; Stadler, Peter F ; Dias, Oscar ; Rocha, Ulisses Nunes da
Source: Life Science Alliance. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, GENÔMICA, ECOLOGIA MICROBIANA
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ABNT
SARAIVA, João Pedro et al. OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes. Life Science Alliance, v. 4, n. 12, p. 1-14, 2021Tradução . . Disponível em: https://doi.org/10.26508/lsa.202101167. Acesso em: 22 dez. 2024.
APA
Saraiva, J. P., Bartholomäus, A., Kallies, R., Gomes, M., Bicalho, M., Kasmanas, J. C., et al. (2021). OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes. Life Science Alliance, 4( 12), 1-14. doi:10.26508/lsa.202101167
NLM
Saraiva JP, Bartholomäus A, Kallies R, Gomes M, Bicalho M, Kasmanas JC, Vogt C, Chatzinotas A, Stadler PF, Dias O, Rocha UN da. OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes [Internet]. Life Science Alliance. 2021 ; 4( 12): 1-14.[citado 2024 dez. 22 ] Available from: https://doi.org/10.26508/lsa.202101167
Vancouver
Saraiva JP, Bartholomäus A, Kallies R, Gomes M, Bicalho M, Kasmanas JC, Vogt C, Chatzinotas A, Stadler PF, Dias O, Rocha UN da. OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes [Internet]. Life Science Alliance. 2021 ; 4( 12): 1-14.[citado 2024 dez. 22 ] Available from: https://doi.org/10.26508/lsa.202101167

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