Neural Isometries: Taming Transformations for Equivariant ML

Neural Information Processing Systems 

Specifically, we regularize the latent space such that maps between encodings preserve a learned inner product and commute with a learned functional operator, in the same manner as rigid-body transformations commute with the Laplacian.

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