MetaFun: meta-learning with iterative functional updates

MetaFun: meta-learning with iterative functional updates

We develop a functional encoder-decoder approach to supervised meta-learning, where labeled data is encoded into an infinite-dimensional functional representation rather than a finite-dimensional one. Furthermore, rather than directly producing the representation, we learn a neural update rule resem...

書誌詳細
主要な著者:	Xu, J, Ton, J-F, Kim, H, Kosiorek, AR, Teh, YW
フォーマット:	Journal article
言語:	English
出版事項:	MLResearch Press 2020

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