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• W2952689920 abstract "We introduce a simple permutation equivariant layer for deep learning with set structure.This type of layer, obtained by parameter-sharing, has a simple implementation and linear-time complexity in the size of each set. We use deep permutation-invariant networks to perform point-could classification and MNIST-digit summation, where in both cases the output is invariant to permutations of the input. In a semi-supervised setting, where the goal is make predictions for each instance within a set, we demonstrate the usefulness of this type of layer in set-outlier detection as well as semi-supervised learning with clustering side-information." @default.
• W2952689920 created "2019-06-27" @default.
• W2952689920 creator A5013695358 @default.
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• W2952689920 date "2016-11-14" @default.
• W2952689920 modified "2023-10-09" @default.
• W2952689920 title "Deep Learning with Sets and Point Clouds" @default.
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• W2952689920 hasPublicationYear "2016" @default.
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