6 citations · 8 across the 9 of their papers we have counts for
3 papers · 1 filter
Surrogate-Guided Adaptive Importance Sampling for Failure Probability Estimation
Ashwin Renganathan, Annie S. Booth
We consider the sample efficient estimation of failure probabilities from expensive oracle evaluations of a limit state function via importance sampling (IS). In contrast to conven…
Modernizing full posterior inference for surrogate modeling of categorical-output simulation experiments
Andrew Cooper, Annie S. Booth, Robert B. Gramacy
Gaussian processes (GPs) are powerful tools for nonlinear classification in which latent GPs are combined with link functions. But GPs do not scale well to large training data. Thi…
Monotonic warpings for additive and deep Gaussian processes
Steven D. Barnett, Lauren J. Beesley, Annie S. Booth +2
Gaussian processes (GPs) are canonical as surrogates for computer experiments because they enjoy a degree of analytic tractability. But that breaks when the response surface is con…