Results 281 to 290 of about 512,942 (311)

Bayesian Monte Carlo.

2003
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.
Rasmussen, C., Ghahramani, Z.
openaire   +2 more sources

Monte-Carlo Kakuro

2010
Kakuro consists in filling a grid with integers that sum up to predefined values. Sums are predefined for each row and column and all integers have to be different in the same row or column. Kakuro can be modeled as a constraint satisfaction problem. Monte-Carlo methods can improve on traditional search methods for Kakuro.
openaire   +1 more source

Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey

Wiley Interdisciplinary Reviews: Computational Statistics, 2021
Jiaxin Zhang
exaly  

Monte Carlo method

2014
Massimiliano Fatica, Gregory Ruetsch
openaire   +1 more source

Quantum Monte Carlo and Related Approaches

Chemical Reviews, 2012
Dmitry Yu Zubarev, William A Lester
exaly  

Monte Carlo methods in geophysical inverse problems

Reviews of Geophysics, 2002
Malcolm Sambridge, Klaus Mosegaard
exaly  

Monte Carlo techniques

Biochemical Society Transactions, 1982
openaire   +2 more sources

Particle Markov Chain Monte Carlo Methods

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2010
Christophe Andrieu, Arnaud Doucet
exaly  

A Monte Carlo Comparison of Relative Importance Methodologies

Organizational Research Methods, 2004
James M Lebreton, Robert E Ployhart
exaly  

Monte Carlo Estimation of Bayesian Credible and HPD Intervals

Journal of Computational and Graphical Statistics, 1999
Ming-Hui Chen, Qi-Man Shao
exaly