69 citations · 105 across the 2 of their papers we have counts for
2 papers
stat.ME2019★ 36 cited
Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data
Daniel Zilber, Matthias Katzfuss
Generalized Gaussian processes (GGPs) are highly flexible models that combine latent GPs with potentially non-Gaussian likelihoods from the exponential family. GGPs can be used in…
stat.ME2018★ 69 cited
Vecchia approximations of Gaussian-process predictions
Matthias Katzfuss, Joseph Guinness, Wenlong Gong +1
Gaussian processes (GPs) are highly flexible function estimators used for geospatial analysis, nonparametric regression, and machine learning, but they are computationally infeasib…