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Bayesian Annealed Sequential Importance Sampling: An Unbiased Version of Transitional Markov Chain Monte Carlo
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The transitional Markov chain Monte Carlo (TMCMC) is one of the efficient algorithms for performing Markov chain Monte Carlo (MCMC) in the context of Bayesian uncertainty quantification in parallel computing architectures. ...
Optimal Sampling Placement in a Gaussian Random Field Based on Value of Information
Publisher: American Society of Civil Engineers
Abstract: In the context of sampling, monitoring, and sensing in infrastructures, there is an interest in algorithms to produce an observation plan that is cost effective, while maximizing the benefits of the new observations. This ...