{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T13:47:58Z","timestamp":1774964878949,"version":"3.50.1"},"reference-count":102,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42430106"],"award-info":[{"award-number":["42430106"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42371468"],"award-info":[{"award-number":["42371468"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["424B2013"],"award-info":[{"award-number":["424B2013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62306033"],"award-info":[{"award-number":["62306033"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"High-performance Computing Platform of Peking University","award":["hpc2306190166"],"award-info":[{"award-number":["hpc2306190166"]}]},{"name":"CTS Scholars Program"},{"name":"Center for Transportation Studies"},{"DOI":"10.13039\/100007249","name":"University of Minnesota","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007249","id-type":"DOI","asserted-by":"publisher"}]},{"name":"DSI Medium/Large Seed Grant"},{"name":"Data Science Initiatives"},{"DOI":"10.13039\/100007249","name":"University of Minnesota","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007249","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1109\/tpami.2025.3625859","type":"journal-article","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T17:33:50Z","timestamp":1761672830000},"page":"2380-2397","source":"Crossref","is-referenced-by-count":2,"title":["A Gravity-Informed Spatiotemporal Transformer for Human Activity Intensity Prediction"],"prefix":"10.1109","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3549-2960","authenticated-orcid":false,"given":"Yi","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China"}]},{"given":"Zhenghong","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3643-018X","authenticated-orcid":false,"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0122-9419","authenticated-orcid":false,"given":"Chaogui","family":"Kang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center of Geographic Information System, China University of Geosciences, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4520-7174","authenticated-orcid":false,"given":"Sijie","family":"Ruan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"}]},{"given":"Di","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Geography, Environment and Society, University of Minnesota, Minneapolis, MN, USA"}]},{"given":"Chengling","family":"Tang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4416-5233","authenticated-orcid":false,"given":"Zhongfu","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Geography, Environment and Society, University of Minnesota, Minneapolis, MN, USA"}]},{"given":"Weiyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5224-4344","authenticated-orcid":false,"given":"Yu","family":"Zheng","sequence":"additional","affiliation":[{"name":"JD Technology & JD Intelligent Cities Research, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3491-5968","authenticated-orcid":false,"given":"Philip S.","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois Chicago, Chicago, IL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0016-2902","authenticated-orcid":false,"given":"Yu","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-023-00469-4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1408439111"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s11442-016-1331-y"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.trpro.2016.05.370"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-021-01113-4"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.03.002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2629592"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3354187"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623628"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2020.0209"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3333824"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117921"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1080\/17538947.2023.2220610"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-023-00667-9"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2019.101403"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2021.1912347"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.102149"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2024.2332908"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-economics-111809-125114"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3221183"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10110-003-0189-4"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1068\/a030001"},{"key":"ref23","first-page":"108","article-title":"The use of entropy maximising models, in the theory of trip distribution, mode split and route split","volume":"3","author":"Wilson","year":"1969","journal-title":"J. Transport Econ. Policy"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2015.05.022"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1086\/694292"},{"key":"ref26","article-title":"Setting the record straight on transformer oversmoothing","author":"Dovonon","year":"2024"},{"key":"ref27","article-title":"Anti-oversmoothing in deep vision transformers via the Fourier domain analysis: From theory to practice","author":"Wang","year":"2022"},{"key":"ref28","article-title":"Revisiting over-smoothing in BERT from the perspective of graph","author":"Shi","year":"2022"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.5040\/9798881820695.ch-006"},{"key":"ref30","first-page":"80233","article-title":"Mitigating over-smoothing in transformers via regularized nonlocal functionals","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Nguyen"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-021-00314-5"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-011-1192-6"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/49.709453"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1080\/00045608.2015.1018773"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2779844"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE55515.2023.00046"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3056502"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615160"},{"key":"ref40","first-page":"75354","article-title":"LargeST: A benchmark dataset for large-scale traffic forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liu"},{"key":"ref41","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","author":"Li","year":"2017"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2935152"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"ref44","first-page":"17804","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Bai"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403118"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3237205"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3532611"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671961"},{"key":"ref49","article-title":"Spatial-temporal transformer networks for traffic flow forecasting","author":"Xu","year":"2020"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5477"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25556"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557702"},{"key":"ref53","article-title":"ST-MLP: A cascaded spatio-temporal linear framework with channel-independence strategy for traffic forecasting","author":"Wang","year":"2023"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.14778\/3641204.3641217"},{"key":"ref55","article-title":"STGformer: Efficient spatiotemporal graph transformer for traffic forecasting","author":"Wang","year":"2024"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3371931"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2130"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2022.103908"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.101971"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294236"},{"key":"ref61","article-title":"Climode: Climate and weather forecasting with physics-informed neural odes","author":"Verma","year":"2024"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2020.0093"},{"key":"ref63","article-title":"AirPhyNet: Harnessing physics-guided neural networks for air quality prediction","author":"Hettige","year":"2024"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3173532"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-annals-V-3-2021-295-2021"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1038\/nature10856"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2018.01.001"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-26752-4"},{"key":"ref69","article-title":"Origin-destination network generation via gravity-guided GAN","author":"Rong","year":"2023"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.65109\/aczl8905"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2024.3386128"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2024.3405970"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2024.104661"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20322"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1016\/j.earscirev.2021.103828"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1007\/BF00328337"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1063\/1.883005"},{"key":"ref78","article-title":"Shaping the world economy; suggestions for an international economic policy","author":"Tinbergen","year":"1962","journal-title":"Int. Executive"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.30875\/abc0167e-en"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2305414120"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1111\/tgis.13168"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3401450"},{"key":"ref83","article-title":"Retentive Network: A successor to transformer for large language models","author":"Sun","year":"2023"},{"key":"ref84","first-page":"933","article-title":"Language modeling with gated convolutional networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Dauphin"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2024.102293"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/PROC.1969.6869"},{"key":"ref87","article-title":"BitNet v2: Native 4-bit activations with Hadamard transformation for 1-bit LLMs","author":"Wang","year":"2025"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482120"},{"key":"ref89","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sutskever"},{"key":"ref90","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"Bai","year":"2018"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref92","article-title":"iTransformer: Inverted transformers are effective for time series forecasting","author":"Liu","year":"2023"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"ref94","first-page":"11906","article-title":"DstaGNN: Dynamic spatial-temporal aware graph neural network for traffic flow forecasting","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lan"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i7.25976"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.101946"},{"key":"ref97","article-title":"STG-Mamba: Spatial-temporal graph learning via selective state space model","author":"Li","year":"2024"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8306.2004.09402005.x"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1080\/19475683.2018.1534890"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.129178"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671451"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-023-04203-7"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/34\/11372200\/11218803.pdf?arnumber=11218803","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T21:05:27Z","timestamp":1770671127000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11218803\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":102,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2025.3625859","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3]]}}}