189 citations · 763 across the 33 of their papers we have counts for
4 papers · 1 filter
Locally anisotropic covariance functions on the sphere
Jian Cao, Jingjie Zhang, Zhuoer Sun +1
Rapid developments in satellite remote-sensing technology have enabled the collection of geospatial data on a global scale, hence increasing the need for covariance functions that…
Scalable Spatio-Temporal Smoothing via Hierarchical Sparse Cholesky Decomposition
Marcin Jurek, Matthias Katzfuss
We propose an approximation to the forward-filter-backward-sampler (FFBS) algorithm for large-scale spatio-temporal smoothing. FFBS is commonly used in Bayesian statistics when wor…
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes
Felix Jimenez, Matthias Katzfuss
Bayesian optimization is a technique for optimizing black-box target functions. At the core of Bayesian optimization is a surrogate model that predicts the output of the target fun…
Scalable Gaussian-process regression and variable selection using Vecchia approximations
Jian Cao, Joseph Guinness, Marc G. Genton +1
Gaussian process (GP) regression is a flexible, nonparametric approach to regression that naturally quantifies uncertainty. In many applications, the number of responses and covari…