Estimating Conditional Probability Densities for Periodic Variables

@inproceedings{Bishop1994EstimatingCP,
  title={Estimating Conditional Probability Densities for Periodic Variables},
  author={Christopher M. Bishop and Claire Legleye},
  booktitle={NIPS},
  year={1994}
}
Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three novel techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite. 

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Mixture density networks. Neural Computing Research Group Report, NCRG/4288, Department of Computer

  • C MBishop
  • 1994

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