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Tntorch: Tensor Network Learning with PyTorch

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dc.contributor.authorBallester, Rafael
dc.contributor.authorUsvyatsov, Mikhail
dc.contributor.authorSchindler, Konrad
dc.contributor.rorhttps://ror.org/02jjdwm75
dc.date.accessioned2025-04-03T16:01:43Z
dc.date.available2025-04-03T16:01:43Z
dc.date.issued2022
dc.description.abstractWe present tntorch, a tensor learning framework that supports multiple decompositions (including Candecomp/Parafac, Tucker, and Tensor Train) under a unified interface. With our library, the user can learn and handle low-rank tensors with automatic differentiation, seamless GPU support, and the convenience of PyTorch’s API. Besides decomposition algorithms, tntorch implements differentiable tensor algebra, rank truncation, crossapproximation, batch processing, comprehensive tensor arithmetics, and more.
dc.description.peerreviewedyes
dc.description.statusPublished
dc.formatapplication/pdf
dc.identifier.citationUsvyatsov, M., Ballester-Ripoll, R., & Schindler, K. (2022). tntorch: Tensor network learning with PyTorch. Journal of Machine Learning Research, 23(208), 1-6.
dc.identifier.issn1533-7928
dc.identifier.urihttps://hdl.handle.net/20.500.14417/3701
dc.issue.number208
dc.journal.titleJournal of Machine Learning Research
dc.language.isoen
dc.page.final6
dc.page.initial1
dc.page.total6
dc.publisherJMLR
dc.relation.departmentApplied Mathematics
dc.relation.entityIE University
dc.relation.schoolIE School of Science & Technology
dc.rightsAttribution 4.0 International
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed
dc.subject.keywordTensor decompositions
dc.subject.keywordPytorch
dc.subject.keywordLow-rank methods
dc.subject.keywordMultilinear algebra
dc.titleTntorch: Tensor Network Learning with PyTorch
dc.typeinfo:eu-repo/semantics/article
dc.version.typeinfo:eu-repo/semantics/acceptedVersion
dc.volume.number23
dspace.entity.typePublication
relation.isAuthorOfPublication6f756541-9eb4-430c-9664-1833c080ce57
relation.isAuthorOfPublication.latestForDiscovery6f756541-9eb4-430c-9664-1833c080ce57
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