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Diego Parente Paiva Mesquita

    20192022

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    Education/Academic qualification

    Tekn. toht., tietotekniikka

    Award Date: 16 Dec 2021

    Bacharel em Computacao, Republica Federativa do Brasil Ministerio da Educacao

    Award Date: 23 Aug 2016

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    • Bayesian Multilateration

      Sampaio de Carvalho Alencar, A., Mattos, C., Pordeus Gomes, J. P. & Mesquita, D., 2022, In: IEEE Signal Processing Letters. 29, p. 962-966

      Research output: Contribution to journalArticleScientificpeer-review

    • Parallel MCMC Without Embarrassing Failures

      Augusto de Souza, D., Parente Paiva Mesquita, D., Kaski, S. & Acerbi, L., 2022, Proceedings of The 25th International Conference on Artificial Intelligence and Statistics. p. 1786-1804 (Proceedings of Machine Learning Research; vol. 151).

      Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

      Open Access
      File
      4 Downloads (Pure)
    • Advances in distributed Bayesian inference and graph neural networks

      Mesquita, D., 2021, Aalto University. 127 p.

      Research output: ThesisDoctoral ThesisCollection of Articles

      Open Access
    • Federated Stochastic Gradient Langevin Dynamics

      El Mekkaoui, K., Parente Paiva Mesquita, D., Blomstedt, P. & Kaski, S., Dec 2021, Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence. p. 1703-1712 10 p. (Proceedings of Machine Learning Research ; no. 161).

      Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

      Open Access
      File
      8 Downloads (Pure)
    • Improving Graph Variational Autoencoders with Multi-Hop Simple Convolutions

      do Nascimento, E. J. F., Souza, A. H. & Mesquita, D., 2021, ESANN 2021 Proceedings - 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 105-110 6 p. (ESANN 2021 Proceedings - 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

      Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

      1 Citation (Scopus)