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ProtoVAE: Prototypical Networks for Unsupervised Disentanglement
Generative modeling and self-supervised learning have in recent years made great strides towards learning from data in a completely unsupervised way.
DOT-VAE: Disentangling One Factor at a Time
One promising approach to this endeavour is the problem of Disentanglement, which aims at learning the underlying generative latent factors, called the factors of variation, of the data and encoding them in disjoint latent representations.
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