Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models

A Generalized Polynomial Chaos - Based Method for Efficient Bayesian Calibration of Uncertain Computational Models

This paper addresses the Bayesian calibration of dynamic models with parametric and structural uncertainties, in particular where the uncertain parameters are unknown/poorly known spatio-temporally varying subsystem models. Independent stationary Gaussian processes with uncertain hyper-parameters describe uncertainties of the model structure and parameters while Karhunnen-Loeve expansion is ado...

The Pseudo - Marginal Approach for Efficient Monte Carlo Computations

We introduce a powerful and flexible MCMC algorithm for stochastic simulation. The method builds on a pseudo-marginal method originally introduced in [Genetics 164 (2003) 1139–1160], showing how algorithms which are approximations to an idealized marginal algorithm, can share the same marginal stationary distribution as the idealized method. Theoretical results are given describing the converge...

Implementing The Generalised Hybrid Monte-Carlo Algorithm

UKQCD’s dynamical fermion project uses the Generalised Hybrid Monte Carlo (GHMC) algorithm to generate QCD gauge configurations for a non-perturbatively O(a) improved Wilson action with two degenerate sea-quark flavours. We describe our implementation of the algorithm on the Cray-T3E, concentrating on issues arising from code verification and performance optimisation, such as parameter tuning, ...

On Monte Carlo and Quasi-Monte Carlo for Matrix Computations

Bayesian Generalised Ensemble Markov Chain Monte Carlo

Bayesian generalised ensemble (BayesGE) is a new method that addresses two major drawbacks of standard Markov chain Monte Carlo algorithms for inference in highdimensional probability models: inapplicability to estimate the partition function and poor mixing properties. BayesGE uses a Bayesian approach to iteratively update the belief about the density of states (distribution of the log likelih...