Performing inference in Bayesian models requires sampling algorithms to ...
Kernel Stein discrepancy (KSD) is a widely used kernel-based measure of
...
Stein variational gradient descent (SVGD) is a deterministic particle
in...
Variational Gaussian process (GP) approximations have become a standard ...
Statistical depth is the act of gauging how representative a point is
co...
We propose a nonparametric two-sample test procedure based on Maximum Me...
Despite the ubiquity of the Gaussian process regression model, few
theor...
Gaussian processes are ubiquitous in statistical analysis, machine learn...