5 Matching Annotations
  1. Jun 2020
  2. May 2020
  3. Sep 2018
    1. conditional distribution for individual components can be constructed

      So the conditional distribution is conditioned on other components?

    1. calculation once again involves inverting a NxN matrix as in the kernel space representation of regression

      this is why we use MCMC or other distribution sampling technique instead

    2. in equation B for the marginal of a gaussian, only the covariance of the block of the matrix involving the unmarginalized dimensions matters! Thus “if you ask only for the properties of the function (you are fitting to the data) at a finite number of points, then inference in the Gaussian process will give you the same answer if you ignore the infinitely many other points, as if you would have taken them all into account!”(Rasmunnsen)

      key insight into Gaussian processes