Written for PyTorch with CUDA compatibility.
Use Case: Instead of doing a multivariate normal sampling (available in torch.distributions.multivariate_normal), one could also do a random sampling within a specified confidence region of the multivariate gaussian function.
Although it will be an approximation, one could obtain a confidence region using the variance across each dimension (diagonal of the covariance matrix). Suppose we define a 3*s boundary (Upto 3 x variance across each dimension is an accepted confidence interval), then EllipsoidSampler can be used to construct such an ellipsoid (with given mean = mu and lengths of axes = axes. This utility will further help sample from within the ellipsoid in a random fashion (instead of a random normal fashion).