Results 291 to 300 of about 1,407,468 (324)

Monte Carlo / Monte Carlo Markov Chain

2014
The Monte Carlo simulation is a versatile method for analyzing the behavior of some activities, plans or processes that involve uncertainty. The method was invented by scientists working on the atomic bomb in the 1940s. It uses randomness to obtain random variable estimates, similarly to the gambling process.
Castellano R., CEDROLA, ELENA
openaire   +1 more source

Monte Carlo and Quasi-Monte Carlo Methods

2013
Chapter 12 discusses Monte Carlo and quasi-Monte Carlo methods and demonstrates how these techniques can be used to compute functionals of multidimensional diffusions. Monte Carlo methods feature prominently in this book, in particular we discuss how to use Lie Symmetry methods to construct unbiased Monte Carlo estimators in Chap. 6, and we discuss how
Jan Baldeaux, Eckhard Platen
openaire   +1 more source

Monte Carlo and Quasi-Monte Carlo Simulation

2014
Is this chapter we will learn the basics of pricing derivatives using simulation methods. We will consider both Monte-Carlo and quasi-Monte Carlo but – of course – with a special emphasis on the latter. The aim of our exposition is not to provide a large toolbox for the quantitative analyst, but to help getting started with the topic. QMC-pricing is an
Gunther Leobacher, Friedrich Pillichshammer   +1 more
openaire   +1 more source

Monte Carlo and quasi-Monte Carlo methods

Acta Numerica, 1998
Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N−1/2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
openaire   +1 more source

�������������� Monte Carlo

2021
- .
openaire   +1 more source

Monte Carlo �������������� ���� ���������� ���������������������� ����������������

2008
In this thesis we focus on the Markov Chain Monte Carlo (MCMC) methods which are useful in simulating mathematical and physical systems. In the introduction we present some classical Monte Carlo algorithms and their historical evolution. We also outline their advantages and disadvantages.
openaire   +1 more source

Monte Carlo ���������������������� ���� �� ���������� ���������������� �������� ���������������������������� ����������������������:

2012
.
openaire   +1 more source

Computational Methods in Heterogeneous Catalysis

Chemical Reviews, 2021
Benjamin W J Chen, Lang Xu, Manos Mavrikakis   +2 more
exaly  

Unbiasing fermionic quantum Monte Carlo with a quantum computer

Nature, 2022
William J Huggins, Nicholas C Rubin, David R Reichman   +2 more
exaly