<ul><li>This paper introduces the quantum deep sets model, expanding the quantum machine learning tool-box by enabling the possibility of learning variadic functions using quantum systems.</li><li>One variant focuses on mapping sets to quantum systems through state vector averaging, allowing the definition of a permutation-invariant variadic model.</li><li>Another variant is useful for ordered sets, such as sequences, and relies on optimal coherification of tristochastic tensors that implement products of mixed states.</li><li>The efficacy and versatility of quantum deep sets and sequences (QDSs) is demonstrated through synthetic problem examples.</li></ul>

Quantum Deep Sets and Sequences

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