wiki/machine-learning/basics/kl-divergence.md

In an inference problem, $p(z\vert x)$, which is used to infer $z$ from $x$. $$ p(z\vert x) = …

Cross entropy is1 $$ H(p, q) = \mathbb E_{p} \left[ -\log q \right]. $$ Cross entropy $H(p, q)$ can …

The f-divergence is defined as1 $$ \operatorname{D}_f = \int f\left(\frac{p}{q}\right) q\mathrm …

The Jensen-Shannon divergence is a symmetric divergence of distributions $P$ and $Q$, $$ …

Mutual information is defined as $$ I(X;Y) = \mathbb E_{p_{XY}} \ln \frac{P_{XY}}{P_X P_Y}. $$ In …

The Fraser information is $$ I_F(\theta) = \int g(X) \ln f(X;\theta) , \mathrm d X. $$ When …

ELBO is an very important concept in variational methods

Latent variable models brings us new insights on identifying the patterns of some sample data.