Wasserstein geometry = quotient geometry of permutation invariance.
In this blog, I explain why this is the natural language for exchangeable particles—and why mean-field neural network training shows up as a W2 gradient flow.
mufan-li.github.io/OT2/
mufan-li.github.io
Everyone Should Learn Optimal Transport, Part 2
In the previous blog post, we saw that optimal transport gives us calculus on the space of probability distributions. In this post, we will continue the core message, but we will also see that Wassers...
