• Corpus ID: 246275932

A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data

@article{Kirkwood2022ADM,
  title={A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data},
  author={Charlie Kirkwood and Theodoros Economou and Henry M. Odbert and Nicolas Pugeault},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.10544}
}
As the costs of sensors and associated IT infrastructure decreases — as exemplified by the Internet of Things — increasing volumes of observational data are becoming available for use by environmental scientists. However, as the number of available observation sites increases, so too does the opportunity for data quality issues to emerge, particularly given that many of these sensors do not have the benefit of official maintenance teams. To realise the value of crowd sourced ‘Internet of Things… 

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