Concept Representation Learning with Contrastive Self-Supervised Learning

Concept-oriented deep learning (CODL) is a general approach to meet the future challenges for deep learning: learning with little or no external supervision, coping with test examples that come from a different distribution than the training examples, and integrating deep learning with symbolic AI.

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Daniel T. Chang (2024). Dataset: Concept Representation Learning with Contrastive Self-Supervised Learning. https://doi.org/10.57702/5gtz2vhl

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2112.05677
Author Daniel T. Chang