152 citations · 762 across the 23 of their papers we have counts for
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A Scalable Method to Exploit Screening in Gaussian Process Models with Noise
Christopher J. Geoga, Michael L. Stein
A common approach to approximating Gaussian log-likelihoods at scale exploits the fact that precision matrices can be well-approximated by sparse matrices in some circumstances. Th…
Scalable Computations for Nonstationary Gaussian Processes
Paul G. Beckman, Christopher J. Geoga, Michael L. Stein +1
Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets…
Vecchia Likelihood Approximation for Accurate and Fast Inference in Intractable Spatial Extremes Models
Raphaël Huser, Michael L. Stein, Peng Zhong
Max-stable processes are the most popular models for high-impact spatial extreme events, as they arise as the only possible limits of spatially-indexed block maxima. However, likel…