A better permutation-equivariance property for set prediction.
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Deep set prediction networks
To predict a set from a vector, use gradient descent to find a set the encodes to that vector.
FSPool: Learning set representations with featurewise sort pooling
Sort in encoder and undo sorting in decoder to avoid responsibility problem in set auto-encoders.
Learning representations of sets through optimized permutations
Learn how to permute a set, then encode permuted set with RNN to obtain a set representation.
Learning to count objects in natural images for visual question answering
Enabling visual question answering models to count by handling overlapping object proposals.