Towards unsupervised representation learning for quantum data: quantum models with inference and generation
A conceptual and mathematical framework for unsupervised representation learning from quantum data is developed, uncovering a hierarchy tied to the positive-partial-transpose (PPT) criterion from entanglement theory and allowing genuinely quantum visible-latent correlations.
Robin Lorenz, Eric Brunner, Marcello Benedetti
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