Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384830735> ?p ?o ?g. }
- W4384830735 abstract "Once developed for quantum theory, tensor networks have been established as a successful machine learning paradigm. Now, they have been ported back to the quantum realm in the emerging field of quantum machine learning to assess problems that classical computers are unable to solve efficiently. Their nature at the interface between physics and machine learning makes tensor networks easily deployable on quantum computers. In this review article, we shed light on one of the major architectures considered to be predestined for variational quantum machine learning. In particular, we discuss how layouts like MPS, PEPS, TTNs and MERA can be mapped to a quantum computer, how they can be used for machine learning and data encoding and which implementation techniques improve their performance." @default.
- W4384830735 created "2023-07-21" @default.
- W4384830735 creator A5047773398 @default.
- W4384830735 creator A5073402824 @default.
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- W4384830735 date "2023-07-01" @default.
- W4384830735 modified "2023-10-14" @default.
- W4384830735 title "Tensor networks for quantum machine learning" @default.
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- W4384830735 doi "https://doi.org/10.1098/rspa.2023.0218" @default.
- W4384830735 hasPublicationYear "2023" @default.
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