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dc.contributor.authorWang, Hanrui
dc.contributor.authorGu, Jiaqi
dc.contributor.authorDing, Yongshan
dc.contributor.authorLi, Zirui
dc.contributor.authorChong, Frederic
dc.contributor.authorPan, David Z.
dc.contributor.authorHan, Song
dc.date.accessioned2022-11-15T16:35:55Z
dc.date.available2022-11-15T16:35:55Z
dc.date.issued2022-07-10
dc.identifier.isbn978-1-4503-9142-9
dc.identifier.urihttps://hdl.handle.net/1721.1/146453
dc.publisherACM|Proceedings of the 59th ACM/IEEE Design Automation Conferenceen_US
dc.relation.isversionofhttps://doi.org/10.1145/3489517.3530400en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceACM|Proceedings of the 59th ACM/IEEE Design Automation Conferenceen_US
dc.titleQuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalizationen_US
dc.typeArticleen_US
dc.identifier.citationWang, Hanrui, Gu, Jiaqi, Ding, Yongshan, Li, Zirui, Chong, Frederic et al. 2022. "QuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalization."
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-11-03T12:24:39Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-11-03T12:24:40Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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