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SUMMARY:Distributional learning: from methodology to applications - Xinwei
  Shen (ETH Zurich)
DTSTART:20241011T130000Z
DTEND:20241011T140000Z
UID:TALK222040@talks.cam.ac.uk
CONTACT:Qingyuan Zhao
DESCRIPTION:Estimating the full (conditional) distribution is crucial to m
 any applications. However\, existing methods such as quantile regression t
 ypically struggle with high-dimensional response variables. To this end\, 
 distributional learning models the target distribution via a generative mo
 del\, which enables inference via sampling. In this talk\, we introduce a 
 distributional learning method called engression. We then demonstrate the 
 applications of engression to several statistical problems including extra
 polation in nonparametric regression\, causal effect estimation\, and dime
 nsion reduction\, as well as scientific problems such as climate downscali
 ng.
LOCATION:Centre for Mathematical Sciences MR12\, CMS
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