19 citations · 22 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 3 cited
Scalable Bayesian Learning with posteriors
Samuel Duffield, Kaelan Donatella, Johnathan Chiu +2
Although theoretically compelling, Bayesian learning with modern machine learning models is computationally challenging since it requires approximating a high dimensional posterior…
stat.ME2013★ 19 cited
Multivariate Gaussian Random Fields Using Systems of Stochastic Partial Differential Equations
Xiangping Hu, Daniel Simpson, Finn Lindgren +1
In this paper a new approach for constructing \emph{multivariate} Gaussian random fields (GRFs) using systems of stochastic partial differential equations (SPDEs) has been introduc…