Raphael Engler

Enabling scalable stochastic gradient-based inference for Gaussian\n processes by employing the Unbiased LInear System SolvEr (ULISSE)

2015 · arXiv (Cornell University)

In applications of Gaussian processes where quantification of uncertainty is\nof primary interest, it is necessary to accurately characterize the posterior\ndistribution over covariance parameters. This paper proposes an adaptation of\nthe Stochastic Gradient Langevin Dynamics algorithm to …