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cs.CV2024
The Entropy Enigma: Success and Failure of Entropy Minimization
Ori Press, Ravid Shwartz-Ziv, Yann LeCun +1
Entropy minimization (EM) is frequently used to increase the accuracy of classification models when they're faced with new data at test time. EM is a self-supervised learning metho…
cs.CV2020★ 18 cited
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer
Ori Press, Tomer Galanti, Sagie Benaim +1
We study the problem of learning to map, in an unsupervised way, between domains A and B, such that the samples b in B contain all the information that exists in samples a in A and…