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stat.ME2023
Propagating moments in probabilistic graphical models with polynomial regression forms for decision support systems
Victoria Volodina, Nikki Sonenberg, Peter Challenor +1
Probabilistic graphical models are widely used to model complex systems under uncertainty. Traditionally, Gaussian directed graphical models are applied for analysis of large netwo…
stat.ME2018
Diagnostic-Driven Nonstationary Emulators Using Kernel Mixtures
Victoria Volodina, Daniel B. Williamson
Weakly stationary Gaussian processes (GPs) are the principal tool in the statistical approaches to the design and analysis of computer experiments (or Uncertainty Quantification).…