In a heroic final push, Soledad Villar (JHU) finished our paper for NeurIPS submission today. We showed that you can make gauge-invariant neural networks without using the irreducible representations of group theory, or any other heavy computational machinery, at least for large classes of groups. Indeed, for all the groups that appear in classical physics (orthogonal group, rotations, Euclidean, Lorentz, Poincaré, permutation). Our contribution is pure math! It is only about machine learning inasmuch as it suggests future methods and simplifications. We will post it to arXiv next week.