Learning Equivariant Functions with Probabilistic Symmetrization for Diverse Group Symmetries

A novel framework for learning equivariant functions by symmetrizing an arbitrary base model using a learned equivariant distribution, which can handle diverse group symmetries including permutations, rotations, and their combinations.