rc.gpf.base§

Contains extensions to gpflow.base.

Classes§

Variance

A non-diagonal Variance Matrix.

Module Contents§

class Variance(value, name='Variance', cholesky_diagonal_lower_bound=CHOLESKY_DIAGONAL_LOWER_BOUND)§

Bases: gpflow.Module

Inheritance diagram of rc.gpf.base.Variance

A non-diagonal Variance Matrix.

Parameters:
  • name (str)

  • cholesky_diagonal_lower_bound (float)

property shape: Tuple[int, int]§

Returns (L,L), which is the shape of self.value and self.cholesky.

Return type:

Tuple[int, int]

property cholesky: tensorflow.Tensor§

The (lower triangular) Cholesky decomposition of the covariance matrix.

Return type:

tensorflow.Tensor

property value§

The covariance matrix, shape (L,L).

property value_to_broadcast§

The covariance matrix, shape (L,1,L,1) ready to broadcast.

value_times_eye(N)§

The cartesian product variance[:L, :L] * eye[:N, :N], transposed.

Parameters:

N (int) – The dimension of the identity matrix we are multiplying by.

Return type:

tensorflow.Tensor

Returns: An [:L, :N, :L, :N] Tensor, after transposition.