has_rsample = True
property loc
property mean
property mode
property scale
support = GreaterThan(lower_bound=0.0)
property variance
LowRankMultivariateNormal
class torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal(loc, cov_factor, cov_diag, validate_args=None)
Bases: "Distribution"
Creates a multivariate normal distribution with covariance matrix
   having a low-rank form parameterized by "cov_factor" and
   "cov_diag":
  covariance_matrix = cov_factor @ cov_factor.T + cov_diag

-[ Example ]-



m = LowRankMultivariateNormal(torch.zeros(2), torch.tensor([[1.], [0.]]), torch.ones(2))
m.sample()  # normally distributed with mean=[0,0], cov_factor=[[1],[0]], cov_diag=[1,1]
   tensor([-0.2102, -0.5429])



Parameters:
      * loc (Tensor) -- mean of the distribution with shape
        batch_shape + event_shape
  * **cov_factor** (*Tensor*) -- factor part of low-rank form of
