A nice way to formulate (most) data augmentations is: a family of functions A = {a} such that our optimized neural network f obeys f(x) ~= f(a(x)). So in this

A nice way to formulate (most) data augmentations is: a family of functions A = {a} such that our optimized neural network f obeys f(x) ~= f(a(x)). So in this case, we're explicitly defining the set of desired invariances.