[D] Integral over neural network input space

I'm wondering if it's possible to compute definite integral over the input space. Assuming the network is designed to have finite integral with Gaussian being the final layer, is there a way to implement this without resorting to sampling? All inputs go from negative infinity to infinity.

compute integral machinelearning negative network neural network sampling space