A Appendix
–Neural Information Processing Systems
Finally, when using different values for P, we can get other group actions. Let us first show that (2) and (3) correspond to a particular case of Cohen et al. This proves (2) and (3). In both subcases, by Lemma 4, θ must be a leaky ReLu function. Given a non-equivariant model, a simple way to let it "learn" to be equivariant is to train it with This doubles the size of the training set, which increases the training time.
Neural Information Processing Systems
Aug-15-2025, 03:08:12 GMT
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