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Engineering the Neural Collapse Geometry of Supervised-Contrastive Loss

Supervised-contrastive loss (SCL) is an alternative to cross-entropy (CE) for classification tasks that makes use of similarities in the embedding space to allow for richer representations.

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Jaidev Gill, Vala Vakilian, Christos Thrampoulidis (2024). Dataset: Engineering the Neural Collapse Geometry of Supervised-Contrastive Loss. https://doi.org/10.57702/arr5v9yv

DOI retrieved: December 3, 2024

Additional Info

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Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2310.00893
Author Jaidev Gill
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Vala Vakilian
Christos Thrampoulidis
Homepage https://arxiv.org/abs/2303.12345