Monte Carlo implementation of Gaussian process models for Bayesian regression and classification

Monte Carlo implementation of Gaussian process models for Bayesian regression and classification

by Radford M. Neal

Book 9702 of Technical report (University of Toronto. Dept. of Statistics) --

1997

Browse books you can read free on Readfeed

No club is reading this yet — be the first to start one

Start a club free

Discuss Monte Carlo implementation of Gaussian process models for Bayesian regression and classification with other readers

Join or start a book club for Monte Carlo implementation of Gaussian process models for Bayesian regression and classification on Readfeed. Live chat, shared reading progress, and AI discussion questions — free to get started.

Frequently asked questions

How do I join a book club for Monte Carlo implementation of Gaussian process models for Bayesian regression and classification?

Sign up free on Readfeed, then browse public clubs or start your own club with Monte Carlo implementation of Gaussian process models for Bayesian regression and classification as the current read. Invite friends with a share link and discuss together with live chat and AI discussion questions.

Can I discuss Monte Carlo implementation of Gaussian process models for Bayesian regression and classification with other readers online?

Yes. Readfeed book clubs let you chat live, share progress, and join discussions about Monte Carlo implementation of Gaussian process models for Bayesian regression and classification with readers worldwide — whether your club is virtual, in-person, or hybrid.

Is Readfeed free?

Yes. Creating an account and joining book clubs is free. Sign up to find readers who love the same books and start discussing today.