pymc.variational.operators.KL#

class pymc.variational.operators.KL(approx, beta=1.0)[source]#

Operator based on Kullback Leibler Divergence

This operator constructs Evidence Lower Bound (ELBO) objective

\[ELBO_\beta = \log p(D|\theta) - \beta KL(q||p)\]

where

\[KL[q(v)||p(v)] = \int q(v)\log\frac{q(v)}{p(v)}dv\]

Parameters:

approx: :class:`Approximation`: Approximation used for inference
beta: float: Beta parameter for KL divergence, scales the regularization term.

Methods

`KL.__init__`(approx[, beta])
`KL.apply`(f)	Operator itself

Attributes