Corpus ID: 189928535

From Incomplete, Dynamic Data to Bayesian Networks

@article{Scutari2019FromID,
  title={From Incomplete, Dynamic Data to Bayesian Networks},
  author={Marco Scutari},
  journal={arXiv: Methodology},
  year={2019}
}
  • Marco Scutari
  • Published 2019
  • Mathematics
  • arXiv: Methodology
  • Bayesian networks are a versatile and powerful tool to model complex phenomena and the interplay of their components in a probabilistically principled way. Moving beyond the comparatively simple case of completely observed, static data, which has received the most attention in the literature, in this paper we will review how Bayesian networks can model dynamic data and data with incomplete observations. Such data are the norm at the forefront of research and applications, and Bayesian networks… CONTINUE READING

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