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Function Contrastive Learning of Transferable Representations

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Abstract

Few-shot-learning seeks to find models that are capable of fast-adaptation to novel tasks. Unlike typical few-shot learning algorithms, we propose a contrastive learning method which is not trained to solve a set of tasks, but rather attempts to find a good representation of the underlying data-generating processes (\emph{functions}). T...More

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Author
Muhammad Waleed Gondal
Muhammad Waleed Gondal
Shruti Joshi
Shruti Joshi
Nasim Rahaman
Nasim Rahaman
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