The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Equivalence of restricted Boltzmann machines and tensor network states
Open accessAbstract
The restricted Boltzmann machine is a fundamental building block of deep learning. The authors demonstrate its equivalence with tensor network states with explicit mappings, thus drawing a constructive connection between deep learning and quantum physics. On one side, deep learning approaches can be used to study novel states of matter. In return, investigations of tensor network states and their expressibility can be adapted to guide neural network architecture design.
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Cites
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Cited by
Expressive power of parametrized quantum circuits
Du, Y., Hsieh, M.-H., Liu, T., & Tao, D. (2020) · Physical Review Research · doi:10.1103/physrevresearch.2.033125 · Cited by 318
Tensor Network Contractions: Methods and Applications to Quantum Many-Body Systems
Ran, S.-J., Tirrito, E., Peng, C., Chen, X., Tagliacozzo, L., Su, G., & Lewenstein, M. (2020) · Lecture Notes in Physics · doi:10.1007/978-3-030-34489-4 · Cited by 176
The Born supremacy: quantum advantage and training of an Ising Born machine
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Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines
Cheng, S., Chen, J., & Wang, L. (2018) · Entropy · doi:10.3390/e20080583 · Cited by 104
Self-citationQuenches near Ising quantum criticality as a challenge for artificial neural networks
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Metadata
- Authors
- Chen, J., Cheng, S., Xie, H., Wang, L., & Xiang, T.
- Venue
- Physical Review B
- Publisher
- American Physical Society (APS)
- Published
- 2018-02-02
- Volume
- 97
- Issue
- 8
- ISSN
- 2469-9950 (ISSN-L)
- 2469-9969
- OpenAlex
- W2582761306
- Cited by
- 243
- References
- 16
- FWCI
- 16.71
- Type
- journal article
- Language
- en
- Open access
- green
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- Chen, J., Cheng, S., Xie, H., Wang, L., & Xiang, T. (2018). Equivalence of restricted Boltzmann machines and tensor network states. Physical Review B. https://doi.org/10.1103/physrevb.97.085104
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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