A better permutation-equivariance property for set prediction.
To predict a set from a vector, use gradient descent to find a set the encodes to that vector.
Sort in encoder and undo sorting in decoder to avoid responsibility problem in set auto-encoders.
Learn how to permute a set, then encode permuted set with RNN to obtain a set representation.
Enabling visual question answering models to count by handling overlapping object proposals.