Universally consistent conformal predictive distributions

Research output: Chapter in Book/Report/Conference proceedingChapter


This paper describes conformal predictive systems that are universally consistent in the sense of being consistent under any data-generating distribution, assuming that the observations are produced independently in the IID fashion. Being conformal, these predictive systems satisfy a natural property of small-sample validity, namely they are automatically calibrated in probability.
Original languageEnglish
Title of host publicationProceedings of Machine Learning Research
EditorsAlex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni Smirnov
Number of pages18
Publication statusPublished - 29 Aug 2019


  • calibration in probability
  • conformal prediction
  • predictive distribution
  • universal consistency

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