{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T06:00:00Z","timestamp":1762408800211,"version":"build-2065373602"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1109\/tpami.2025.3594226","type":"journal-article","created":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T18:31:16Z","timestamp":1753986676000},"page":"11022-11039","source":"Crossref","is-referenced-by-count":0,"title":["HL-HGAT: Heterogeneous Graph Attention Network via Hodge-Laplacian Operator"],"prefix":"10.1109","volume":"47","author":[{"given":"Jinghan","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, National University of Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6814-6362","authenticated-orcid":false,"given":"Qiufeng","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8249-3192","authenticated-orcid":false,"given":"Pengli","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National University of Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5926-7100","authenticated-orcid":false,"given":"Yijun","family":"Bian","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National University of Singapore, Singapore"}]},{"given":"Nanguang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National University of Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2852-9670","authenticated-orcid":false,"given":"Moo K.","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Medical Informatics, The University of Wisconsin-Madison, Madison, WI, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0215-6338","authenticated-orcid":false,"given":"Anqi","family":"Qiu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National University of Singapore, Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref3","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kipf","year":"2017"},{"key":"ref4","article-title":"Graph attention networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Veli\u010dkovi\u0107","year":"2018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s43246-022-00315-6"},{"key":"ref6","first-page":"1263","article-title":"Neural message passing for quantum chemistry","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gilmer","year":"2017"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102370"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3218745"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.01.043"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117921"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16533"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3535101"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3322959"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevD.103.032005"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICESC51422.2021.9532631"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2005.03.001"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-34048-2_24"},{"key":"ref18","first-page":"396","article-title":"Handwritten digit recognition with a back-propagation network","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"2","author":"LeCun","year":"1989"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118774"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102233"},{"article-title":"Residual gated graph ConvNets","year":"2017","author":"Bresson","key":"ref21"},{"key":"ref22","first-page":"14501","article-title":"Recipe for a general, powerful, scalable graph transformer","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Ramp\u00e1\u0161ek","year":"2022"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref24","article-title":"Spectral networks and deep locally connected networks on graphs","volume-title":"Proc. 2nd Int. Conf. Learn. Representations","author":"Bruna","year":"2014"},{"key":"ref25","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Defferrard","year":"2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06006-6"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/369"},{"key":"ref28","first-page":"7534","article-title":"Edge representation learning with hypergraphs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Jo"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.93.062311"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.2981920"},{"article-title":"Simplicial neural networks","year":"2020","author":"Ebli","key":"ref31"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746017"},{"key":"ref33","first-page":"1026","article-title":"Weisfeiler and Lehman go topological: Message passing simplicial networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bodnar","year":"2021"},{"key":"ref34","article-title":"Simplicial attention networks","volume-title":"Proc. ICLR Workshop Geometrical Topological Representation Learn.","author":"Goh","year":"2022"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TSIPN.2024.3485473"},{"article-title":"Dual-primal graph convolutional networks","year":"2018","author":"Monti","key":"ref36"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-34048-2_22"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3190922"},{"key":"ref39","article-title":"Hierarchical graph representation learning with differentiable pooling","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Ying"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2021.3081010"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3062794"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096866"},{"key":"ref43","first-page":"874","article-title":"Spectral clustering with graph neural networks for graph pooling","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bianchi","year":"2020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.2000.892133"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10443-0_38"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2363884"},{"volume-title":"The NIST Handbook of Mathematical Functions","year":"2010","author":"Olver","key":"ref47"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2967451"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1115"},{"issue":"43","key":"ref50","first-page":"1","article-title":"Benchmarking graph neural networks","volume":"24","author":"Dwivedi","year":"2023","journal-title":"J. Mach. Learn. Res."},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"Kingma","key":"ref51"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3455008"},{"key":"ref53","article-title":"Fast graph representation learning with PyTorch geometric","volume-title":"Proc. Workshop Representation Learn. Graphs Manifolds","author":"Fey","year":"2019"},{"article-title":"The travelling salesman problem and related problems","year":"1978","author":"Gavish","key":"ref54"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1515\/9780691187563-011"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref57","first-page":"22326","article-title":"Long range graph benchmark","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Dwivedi","year":"2022"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1080\/01431160600746456"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref59"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1021\/ci3001277"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv1114"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.ddtec.2020.11.009"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1007"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1021\/acsomega.7b01102"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/s10822-019-00271-3"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1186\/1758-2946-1-8"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2017.10.010"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1162\/jocn.2009.21407"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1111\/mono.12038"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2019.00789"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2016.178"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1159\/000328465"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2017.04.030"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1017\/S0140525X07001185"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.02.036"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.08.043"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72120-5_67"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/34\/11230086\/11106311.pdf?arnumber=11106311","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T05:47:38Z","timestamp":1762408058000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11106311\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":78,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2025.3594226","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"type":"print","value":"0162-8828"},{"type":"electronic","value":"2160-9292"},{"type":"electronic","value":"1939-3539"}],"subject":[],"published":{"date-parts":[[2025,12]]}}}