Supplement to Amortized Projection Optimization for Sliced Wasserstein Generative Models

PRW can be seen as the generalization of Max-SW since PRW with k =1 is equivalent to Max-SW. Similar to Max-SW, the optimization of PRW is solved by using projected gradient ascent. The detailed of the algorithm is given in Algorithm 4. We would like to recall that other methods of optimization have also been used to solved PRW such as Riemannian optimization [28], block coordinate descent [21]. However, in this paper, we consider the original and simplest method which is projected gradient ascent.