# Representation

Centered Kernel Alignment (CKA) is a similarity metric designed to measure the similarity of between representations of features in neural networks.

Given two kernels of the feature representations $K=k(x,x)$ and $L=l(y,y)$, HSIC is defined as12  …

A good representation should be able to separate different instances and cluster similar instances.