Sobol sequences are an example of low discrepancy quasi-random sequences. This implementation of an engine for Sobol sequences is capable of sampling sequences up to a maximum dimension of 1111. It uses directio
torch.normal(mean=0.0, std, out=None) → Tensor torch.normal(mean, std=1.0, out=None) → Tensor torch.normal(mean, std, size, *, out=None) → Tensor torch.rand(*size, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor torch.rand_like(input, ...
# Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy # Sutherland et al. # # As we just use this to test, note that we do not square the bandwith in the # denominiator. # # [1] https://github.com/dougalsutherland/opt-mmd def shogun_mmd(X, Y, kernel_width...