I'm trying to get a value for a correlation between a function input and its output. One brute force way to get this is to sample the entire space and find the standard deviation of the resulting outputs.
Is there a less expensive way to find this correlation, perhaps by differentiating the equation?
For more context, I'm trying to see how much a particular input affects each output of a neural network (nothing to do with tuning weights).