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Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar * 1 Li Jing * 1 Ishan Misra 1 Yann LeCun 1 2 Stephane Deny 1
Abstract
Self-supervised learning (SSL) is rapidly closing
the gap with supervised methods on large com-
puter vision benchmarks. A successful approach
to SSL is to learn embeddings which are invariant
to distortions of the input sample. However, a
recurring issue with this approach is the existence
of trivial constant solutions. Most cu ...
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