From Probabilistic Graphical Models to Generalized Tensor Networks for 
Supervised Learning

Glasser, Ivan; Pancotti, Nicola; Cirac, J. Ignacio

doi:10.1109/ACCESS.2020.2986279

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From Probabilistic Graphical Models to Generalized Tensor Networks for Supervised Learning

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Glasser, Ivan
Theory, Max Planck Institute of Quantum Optics, Max Planck Society;
MCQST - Munich Center for Quantum Science and Technology, External Organizations;

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Pancotti, Nicola
Theory, Max Planck Institute of Quantum Optics, Max Planck Society;
IMPRS (International Max Planck Research School), Max Planck Institute of Quantum Optics, Max Planck Society;
MCQST - Munich Center for Quantum Science and Technology, External Organizations;

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Cirac, J. Ignacio
Theory, Max Planck Institute of Quantum Optics, Max Planck Society;
MCQST - Munich Center for Quantum Science and Technology, External Organizations;

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Glasser, I., Pancotti, N., & Cirac, J. I. (2020). From Probabilistic Graphical Models to Generalized Tensor Networks for Supervised Learning. IEEE Access, 8, 68169-68182. doi:10.1109/ACCESS.2020.2986279.

Cite as: https://hdl.handle.net/21.11116/0000-0006-5922-0

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