After we posted this paper on gauge-equivariant methods for machine learning, we got referee comments that maybe what we are doing isn't gauge. So we spent a lot of time working on gauge! What we are doing can be gauge, but there are additional things to add to make that clear. We are clarifying, but maybe for a next contribution in which we really do full gauge invariance, and things like parallel transport.
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