Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems

@article{Rodrigues2020BeyondED,
  title={Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems},
  author={Filipe Rodrigues and F. Pereira},
  journal={IEEE transactions on neural networks and learning systems},
  year={2020}
}
  • Filipe Rodrigues, F. Pereira
  • Published 2020
  • Computer Science, Mathematics, Medicine
  • IEEE transactions on neural networks and learning systems
  • Spatiotemporal problems are ubiquitous and of vital importance in many research fields. Despite the potential already demonstrated by deep learning methods in modeling spatiotemporal data, typical approaches tend to focus solely on conditional expectations of the output variables being modeled. In this article, we propose a multioutput multiquantile deep learning approach for jointly modeling several conditional quantiles together with the conditional expectation as a way to provide a more… CONTINUE READING
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