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On Invariance and Selectivity in Representation Learning

Title:

On Invariance and Selectivity in Representation Learning
Publication Type:
CBMM Memo
Year of Publication:
2015
Date Published:
03/2015
Abstract:

We discuss data representation which can be learned automatically from data, are invariant to transformations, and at the same time selective, in the sense that two points have the same representation only if they are one the transformation of the other. The mathematical results here sharpen some of the key claims of i-theory, a recent theory of feedforward processing in sensory cortex.

Citation Key:
13
CBMM Memo No:
29