Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions

Samantha Chen, Yusu Wang

Learning distance functions between complex objects, such as the Wasserstein distance to compare point sets, is a common goal in machine learning applications. However, functions o…