Description: This seminar will be an introduction to Bayesian methods in model uncertainty quantification. It will begin with a brief overview of Bayes’ theorem and modern methods used to leverage it, specifically Markov Chain Monte Carlo. Following this a simple example will be discussed to build up the audience’s intuition for Bayesian statistical approach to modeling. Lastly, computational resources will be provided for implementing Bayesian modeling along with tips and strategies for parallelizing the otherwise serial computations of MCMC.

Presenter(s): Taylor Whitehead, GDIT / PET Location: Webcast Date & Time: May 21, 2024, 2:00p - 3:30p ET

Controlled by: DoD HPCMP Controlled by: PET Program CUI Category: OPSEC Limited Dissemination Control: FEDCON POC: Mr. Ronald Hedgepeth, pet@hpc.mil

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CUI