Graph isomorphism testing gives us a way to quantify the representational power of different learning approaches

Given 2 learned representations z_g1 and z_g2 for two corresponding graphs:

• a "perfect" algorithm would have z_g1 = z_g2 if and only if g1 is isomorphic to g2

However, there is no "perfect" representation learning algorithm, but there are several ways to connect it to graph isomorphism testing and approximate its power, such as the The Weisfieler-Lehman (WL) Algorithm