Journal article
Duality of graphical models and tensor networks
- Abstract:
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In this article we show the duality between tensor networks and undirected graphical models with discrete variables. We study tensor networks on hypergraphs, which we call tensor hypernetworks. We show that the tensor hypernetwork on a hypergraph exactly corresponds to the graphical model given by the dual hypergraph. We translate various notions under duality. For example, marginalization in a graphical model is dual to contraction in the tensor network. Algorithms also translate under duali...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Accepted manuscript, pdf, 474.6KB)
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- Publisher copy:
- 10.1093/imaiai/iay009
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Authors
Bibliographic Details
- Publisher:
- Oxford University Press Publisher's website
- Journal:
- Information and Inference Journal website
- Volume:
- 8
- Issue:
- 2
- Pages:
- 273-288
- Publication date:
- 2018-06-21
- Acceptance date:
- 2018-04-30
- DOI:
- EISSN:
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2049-8772
- ISSN:
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2049-8764
- Source identifiers:
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1027140
Item Description
- Keywords:
- Pubs id:
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pubs:1027140
- UUID:
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uuid:274edc9a-687f-456f-ab69-86339bdb0524
- Local pid:
- pubs:1027140
- Deposit date:
- 2019-07-27
Terms of use
- Copyright holder:
- Robeva and Seigal
- Copyright date:
- 2018
- Notes:
- © The Author(s) 2018. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved. This is the accepted manuscript version of the article. The final version is available online from Oxford University Press at: 10.1093/imaiai/iay009
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