509 citations · 3.2k across the 61 of their papers we have counts for
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Sequential Bayesian experimental design for calibration of expensive simulation models
Özge Sürer, Matthew Plumlee, Stefan M. Wild
Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator o…
Constructing a simulation surrogate with partially observed output
Moses Y-H. Chan, Matthew Plumlee, Stefan M. Wild
Gaussian process surrogates are a popular alternative to directly using computationally expensive simulation models. When the simulation output consists of many responses, dimensio…
Scalable Statistical Inference of Photometric Redshift via Data Subsampling
Arindam Fadikar, Stefan M. Wild, Jonas Chaves-Montero
Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models…
Modeling an Augmented Lagrangian for Blackbox Constrained Optimization
Robert B. Gramacy, Genetha A. Gray, Sebastien Le Digabel +4
Constrained blackbox optimization is a difficult problem, with most approaches coming from the mathematical programming literature. The statistical literature is sparse, especially…