Non-asymptotic convergence bounds for Wasserstein approximation using point clouds
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds
Several issues in machine learning and inverse problems require to generate discrete data, as if sampled from a model probability distribution. A common way to do so relies on the construction of a uniform probability distribution over a set of $N$ points which minimizes the Wasserstein distance to the model …