NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:104
Title:Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance

The reviewers liked the paper and voted for an accept that was confirmed following authors feedback. But the discussion highlighted the fact that the result do not discuss the problem of sampling on the unit sphere that needs to be done when actually learning generative models. It will probably add some variance in practice and should be at least discussed in the final paper and investigated in future works.