University of Cambridge > Talks.cam > Statistics > Distributional learning: from methodology to applications

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Distributional learning: from methodology to applications

Download to your calendar using vCal

If you have a question about this talk, please contact Qingyuan Zhao .

Estimating the full (conditional) distribution is crucial to many applications. However, existing methods such as quantile regression typically struggle with high-dimensional response variables. To this end, distributional learning models the target distribution via a generative model, 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 extrapolation in nonparametric regression, causal effect estimation, and dimension reduction, as well as scientific problems such as climate downscaling.

This talk is part of the Statistics series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Mcafee Activate Online Event on Zoom Beyond Profit Think Tank

Other talks

Tea and Coffee Break Seminars in Cancer The Neurophenomenology of Surrender: Agency, Renewal, and Social Engagement in Speaking in Tongues Christmas Social Evening & Annual General Meeting Cambridge Reading Group on Reproduction: Professor Sara Brill CSAR lecture: Decarbonizing road freight (TBC)
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity