code: def variational_expectations(self, Fmu, Fvar, Y, epsilon=None):
          r
          return self._mc_quadrature(self.logp, Fmu, Fvar, Y=Y, epsilon=epsilon)
docs: r"""
          Compute the expected log density of the data, given a Gaussian
          distribution for the function values.
  
          if
              q(f) = N(Fmu, Fvar)  - Fmu: N x D  Fvar: N x D
  
          and this object represents
  
              p(y|f)  - Y: N x 1
  
          then this method computes
  
             \int (\log p(y|f)) q(f) df.
  
  
          Here, we implement a default Monte Carlo quadrature routine.