The core idea:
For a piece of random Gaussian noise and an input ,
On the line joining these two points, we can have where,
Train a network that can predict , which is nothing but:
The loss function looks like:
What does this network allow us to do? Now, we can simply supply an image of pure Gaussian noise and follow the networkβs predicted velocity for a certain distance over multiple steps. This is Euler integration.