Carl Edward Rasmussen, Zoubin Ghahramani  Home/Search
Context
Related
| gatsby.ucl.ac.uk/~edward/pu...bmc.ps.gz Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: gatsby.ucl.ac.uk/~edward/pub/ (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: We investigate Bayesian alternatives to classical Monte Carlo methods for evaluating integrals. Bayesian Monte Carlo (BMC) allows the incorporation of prior knowledge, such as smoothness of the integrand, into the estimation. In a simple problem we show that this outperforms any classical importance sampling method. We also attempt more challenging multidimensional integrals involved in computing marginal likelihoods of statistical models (a.k.a. partition functions and model evidences)... (Update)
Similar documents (at the sentence level):
77.4%: Bayesian Monte Carlo - Carl Edward Rasmussen (Correct)
Similar documents based on text: More All
0.8: Infinite Mixtures of Gaussian Process Experts - Rasmussen, Ghahramani (2002) (Correct)
0.6: Occam's Razor - Rasmussen, Ghahramani (2001) (Correct)
0.5: A Unifying Review of Linear Gaussian Models - Roweis, Ghahramani (1999) (Correct)
BibTeX entry: (Update)
@misc{ rasmussen-bayesian,
author = "Carl Edward Rasmussen and Zoubin Ghahramani",
title = "Bayesian Monte Carlo",
url = "citeseer.ist.psu.edu/532815.html" }
Citations not processed or no citations identified.
Documents on the same site (http://www.gatsby.ucl.ac.uk/~edward/pub/): More
Bayesian modelling of fMRI time series - Højen-Sørensen, Hansen, al. (2000) (Correct)
Infinite Mixtures of Gaussian Process Experts - Rasmussen, Ghahramani (2002) (Correct)
The Infinite Hidden Markov Model - Beal, Ghahramani, Rasmussen (2002) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC