{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T21:40:15Z","timestamp":1742593215183,"version":"3.40.2"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["SCC-2218809"],"award-info":[{"award-number":["SCC-2218809"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,24]]},"DOI":"10.1109\/itsc58415.2024.10920273","type":"proceedings-article","created":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T19:00:11Z","timestamp":1742583611000},"page":"621-626","source":"Crossref","is-referenced-by-count":0,"title":["Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs"],"prefix":"10.1109","author":[{"given":"Zhaobin","family":"Mo","sequence":"first","affiliation":[{"name":"Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10025"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Columbia University,Department of Electrical Engineering,New York,NY,USA,10025"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baohua","family":"Yan","sequence":"additional","affiliation":[{"name":"Columbia University,Department of Applied Physics and Applied Mathematics,New York,NY,USA,10025"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Data Science Institute, Columbia University,New York,NY,USA,10027"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuan","family":"Di","sequence":"additional","affiliation":[{"name":"Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10025"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC57777.2023.10422526"},{"key":"ref2","article-title":"St-mlp: A cascaded spatio-temporal linear framework with channel-independence strategy for traffic forecasting","author":"Wang","year":"2023","journal-title":"arXiv preprint"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557437"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-022-10750-8"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20362"},{"key":"ref6","article-title":"Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting","author":"Yu","year":"2017","journal-title":"arXiv preprint"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3587716.3587748"},{"key":"ref8","first-page":"17 804","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume":"33","author":"Bai","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20342"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411894"},{"key":"ref12","first-page":"6074","article-title":"Dynamic graph neural networks under spatio-temporal distribution shift","volume":"35","author":"Zhang","year":"2022","journal-title":"Advances in neural information processing systems"},{"key":"ref13","article-title":"Deciphering spatio-temporal graph forecasting: A causal lens and treatment","volume":"36","author":"Xia","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/computers13060151"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16542"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2955794"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3673227"},{"key":"ref18","first-page":"1418","article-title":"Pi-neugode: Physics-informed graph neural ordinary differential equations for spatiotemporal trajectory prediction","volume-title":"Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems","author":"Mo"},{"key":"ref19","article-title":"Causal imitation learning via inverse reinforcement learning","volume-title":"The Eleventh International Conference on Learning Representations","author":"Ruan","year":"2023"},{"key":"ref20","first-page":"22 131","article-title":"Learning causally invariant representations for out-of-distribution generalization on graphs","volume":"35","author":"Chen","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref21","first-page":"24 934","article-title":"Debiasing graph neural networks via learning disentangled causal substructure","volume":"35","author":"Fan","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref22","article-title":"Model-powered conditional independence test","volume":"30","author":"Sen","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1023\/A:1021193827501","article-title":"Conditional independence test for weights-of-evidence modeling","volume":"11","author":"Agterberg","year":"2002","journal-title":"Natural Resources Research"},{"key":"ref24","first-page":"132","article-title":"A permutation-based kernel conditional independence test","author":"Doran","year":"2014","journal-title":"UAI"},{"key":"ref25","article-title":"Kernel-based conditional independence test and application in causal discovery","author":"Zhang","year":"2012","journal-title":"arXiv preprint"},{"key":"ref26","first-page":"7502","article-title":"Necessary and sufficient conditions for causal feature selection in time series with latent common causes","volume-title":"International Conference on Machine Learning","author":"Mastakouri"}],"event":{"name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","start":{"date-parts":[[2024,9,24]]},"location":"Edmonton, AB, Canada","end":{"date-parts":[[2024,9,27]]}},"container-title":["2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10919469\/10919190\/10920273.pdf?arnumber=10920273","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T21:10:23Z","timestamp":1742591423000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10920273\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,24]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/itsc58415.2024.10920273","relation":{},"subject":[],"published":{"date-parts":[[2024,9,24]]}}}