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Set Interdependence Transformer: Set-to-Sequence Neural Networks for Permutation Learning and Structure Prediction
The task of learning to map an input set onto a permuted sequence of its elements is challenging for neural networks.
Set-to-Sequence Methods in Machine Learning: a Review
Machine learning on sets towards sequential output is an important and ubiquitous task, with applications ranging from language modeling and meta-learning to multi-agent strategy games and power grid optimization.
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