Bottleneck of computing Exact Gaussian Process Suppose we have n-dimensional Gaussian Process below which consist of n number of data. To represent this distribution, n-dimensional covariance matrix is used. And to infer posterior distribution, the inverted covariance matrix should be computed. Since the Exact GP uses n-number of data as it is for representing distribution, … Continue reading Inducing Points and Variational Inference in Gaussian Process