Goto

Collaborating Authors

 mak ovsjanikov








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.


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.