Sliced Wasserstein Sketches with Error Certificates
Compact representations that support geometrically meaningful comparisons are valuable for learning from probability distributions. We study optimal, free-weight $M$-atom quantization of one-dimensional probability measures in quadratic Wasserstein distance and extend it to higher dimensions via…
By Elaheh Akbari, James Liu, Keaton Hamm, Soheil KolouriarXiv cs.LG
Read the full story
Originally published by arXiv cs.LG on Oct 16, 2026.
Comments
Sign in to join the discussion.