184 citations · 540 across the 36 of their papers we have counts for
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stat.ME2016★ 184 cited
Practical heteroskedastic Gaussian process modeling for large simulation experiments
Mickael Binois, Robert B. Gramacy, Michael Ludkovski
We present a unified view of likelihood based Gaussian progress regression for simulation experiments exhibiting input-dependent noise. Replication plays an important role in that…
stat.ME2016
Gaussian Process Models for Mortality Rates and Improvement Factors
Mike Ludkovski, Jimmy Risk, Howard Zail
We develop a Gaussian process ("GP") framework for modeling mortality rates and mortality improvement factors. GP regression is a nonparametric, data-driven approach for determinin…