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Conference Paper

Expressive power of tensor-network factorizations for probabilistic modeling

MPS-Authors
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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;

/persons/resource/persons60441

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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Citation

Glasser, I., Sweke, R., Pancotti, N., Eisert, J., & Cirac, J. I. (2019). Expressive power of tensor-network factorizations for probabilistic modeling. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, & E. Fox (Eds.), Advances in Neural Information Processing Systems. Neural Information Processing Systems Foundation, Inc. ( NIPS ). Retrieved from https://papers.nips.cc/paper/8429-expressive-power-of-tensor-network-factorizations-for-probabilistic-modeling.


Cite as: https://hdl.handle.net/21.11116/0000-0006-8EBA-9
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