I was wondering if it would be interesting to have operations like +, *, etc. on distribution from pytorch.distributions?
e.g.
X  = torch.distributions.Normal(loc=1, scale=1)
Y  = torch.distributions.Normal(loc=0, scale=2)
(X+Y).mean()
(X*Y).std()

of course one could sample to simulate the X, Y and then perform the operations on the equivalent samples, but  I was wondering 1) if that is a good approximation and 2) would the above example be feasible?