Jensen-Shannon divergence

The Jensen-Shannon divergence (also called the information radius (IRaD) or the total divergence to the average) is another measure of similarity between two probability distributions. It is based on KL divergence. Unlike KL divergence, however, JS divergence is symmetric in nature and can be used to measure the distance between two probability distributions. If we take the square root of the Jensen-Shannon divergence, we get the Jensen-Shannon distance, so it is therefore a distance metric.

The following equation represents the Jensen-Shannon divergence between two probability distributions, p and q:

In the preceding equation, (p+q) is the midpoint measure, while  is the Kullback-Leibler divergence.

Now that we have learned about the KL divergence and the Jenson-Shannon divergence, let's discuss the Nash equilibrium for GANs.