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cs.LG2026
Radial-VCReg: More Informative Representation Learning Through Radial Gaussianization
Yilun Kuang, Yash Dagade, Deep Chakraborty +4
Self-supervised learning aims to learn maximally informative representations, but explicit information maximization is hindered by the curse of dimensionality. Existing methods lik…
cs.LG2024
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization
Deep Chakraborty, Yann LeCun, Tim G. J. Rudner +1
A number of different architectures and loss functions have been applied to the problem of self-supervised learning (SSL), with the goal of developing embeddings that provide the b…