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# BYOL

Bootstrap Your Own Latent - A framework that tries to minimize similarity loss between a pair of convolutional networks trained together, one seeing the unperturbed version of a sample, and the other seeing its perturbed pair

<figure><img src="/files/fYPVCnxKCepAFHxOde1L" alt=""><figcaption></figcaption></figure>

References:

1. Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko: “Bootstrap your own latent: A new approach to self-supervised Learning”, 2020; [arXiv:2006.07733](http://arxiv.org/abs/2006.07733).


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