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dc.contributor.authorLiu, Shuncheng
dc.contributor.authorChen, Xu
dc.contributor.authorWu, Ziniu
dc.contributor.authorDeng, Liwei
dc.contributor.authorSu, Han
dc.contributor.authorZheng, Kai
dc.date.accessioned2022-11-16T14:36:38Z
dc.date.available2022-11-16T14:36:38Z
dc.date.issued2022-10-17
dc.identifier.isbn978-1-4503-9236-5
dc.identifier.urihttps://hdl.handle.net/1721.1/146500
dc.publisherACM|Proceedings of the 31st ACM International Conference on Information and Knowledge Management CD-ROMen_US
dc.relation.isversionofhttps://doi.org/10.1145/3511808.3557345en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceACM|Proceedings of the 31st ACM International Conference on Information and Knowledge Management CD-ROMen_US
dc.titleHeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Trafficen_US
dc.typeArticleen_US
dc.identifier.citationLiu, Shuncheng, Chen, Xu, Wu, Ziniu, Deng, Liwei, Su, Han et al. 2022. "HeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Traffic."
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_POLICY
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.updated2022-11-03T12:48:46Z
dc.language.rfc3066en
dc.rights.holderACM
dspace.date.submission2022-11-03T12:48:46Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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