We propose the use of data symmetries, in the sense of equivalences under signal transformations, as priors for learning symmetry-adapted data representations, i.e., representations that are equivariant to these transformations.
Learning representations that account for data symmetries
Fabio Anselmi;
2018-01-01
Abstract
We propose the use of data symmetries, in the sense of equivalences under signal transformations, as priors for learning symmetry-adapted data representations, i.e., representations that are equivariant to these transformations.File in questo prodotto:
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