{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T10:56:53Z","timestamp":1753441013909,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T00:00:00Z","timestamp":1743379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EuroTech Universities Alliance"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,3,31]]},"DOI":"10.1145\/3672608.3707852","type":"proceedings-article","created":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T18:26:21Z","timestamp":1747247181000},"page":"1590-1599","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Leveraging Contrastive Learning and Spatial Encoding for Prediction in Traffic Networks with Expanding Infrastructure"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4815-4091","authenticated-orcid":false,"given":"You","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4027-4351","authenticated-orcid":false,"given":"Marwan","family":"Hassani","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, Netherlands"}]}],"member":"320","published-online":{"date-parts":[[2025,5,14]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Advances in Neural Information Processing Systems","volume":"33","author":"Lina Yao LEI BAI","year":"2020","unstructured":"LEI BAI, Lina Yao, Can Li, Xianzhi Wang, and Can Wang. 2020. Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting. In Advances in Neural Information Processing Systems, Vol. 33. Curran Associates, Inc., 17804\u201317815."},{"key":"e_1_3_2_1_2_1","unstructured":"Shaojie Bai J. Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling."},{"key":"e_1_3_2_1_3_1","unstructured":"Ting Chen Simon Kornblith Mohammad Norouzi and Geoffrey Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. In ICML (2020-11-21). PMLR 1597\u20131607."},{"key":"e_1_3_2_1_4_1","volume-title":"IDEAS'24","author":"Choudhary Himanshu","year":"2024","unstructured":"Himanshu Choudhary, Ahmad B Alkhodre, and Marwan Hassani. 2024. Outlier-Weighted Traffic Flow Prediction using Online Autoencoders. In IDEAS'24. Springer, to appear."},{"key":"e_1_3_2_1_5_1","volume-title":"Autoencoder-based Continual Outlier Correlation Detection for Real-Time Traffic Flow Prediction. In SAC'24","author":"Choudhary Himanshu","year":"2024","unstructured":"Himanshu Choudhary and Marwan Hassani. 2024. Autoencoder-based Continual Outlier Correlation Detection for Real-Time Traffic Flow Prediction. In SAC'24. ACM, 218\u2013220."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/0146-664X(80)90054-4"},{"key":"e_1_3_2_1_7_1","first-page":"3844","article-title":"Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering","volume":"29","author":"Defferrard Micha\u00ebl","year":"2016","unstructured":"Micha\u00ebl Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. In Advances in Neural Information Processing Systems, Vol. 29. 3844\u20133852.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMPSAC51774.2021.00039"},{"key":"e_1_3_2_1_9_1","unstructured":"Kaiming He Haoqi Fan Yuxin Wu Saining Xie and Ross Girshick. 2020. Momentum Contrast for Unsupervised Visual Representation Learning. In CVPR. 9726\u20139735."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2611567"},{"key":"e_1_3_2_1_12_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2017","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1017\/9781108999687"},{"key":"e_1_3_2_1_14_1","volume-title":"Austin Reiter, and Gregory D. Hager","author":"Lea Colin","year":"2017","unstructured":"Colin Lea, Michael D. Flynn, Rene Vidal, Austin Reiter, and Gregory D. Hager. 2017. Temporal Convolutional Networks for Action Segmentation and Detection. In CVPR. 156\u2013165."},{"key":"e_1_3_2_1_15_1","volume-title":"Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution. ACM Transactions on Knowledge Discovery from Data 17, 1","author":"Li Fuxian","year":"2023","unstructured":"Fuxian Li, Jie Feng, Huan Yan, Guangyin Jin, Fan Yang, Funing Sun, Depeng Jin, and Yong Li. 2023. Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution. ACM Transactions on Knowledge Discovery from Data 17, 1 (2023), 9:1\u20139:21."},{"key":"e_1_3_2_1_16_1","unstructured":"Yaguang Li Rose Yu Cyrus Shahabi and Yan Liu. 2018. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3557915.3560939"},{"key":"e_1_3_2_1_18_1","volume-title":"Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems. In ECML PKDD (Lecture Notes in Computer Science","volume":"537","author":"Mertens Tom","year":"2022","unstructured":"Tom Mertens and Marwan Hassani. 2022. Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems. In ECML PKDD (Lecture Notes in Computer Science, Vol. 13718). Springer, 521\u2013537."},{"volume-title":"The Fast Fourier Transform","author":"Nussbaumer Henri J.","key":"e_1_3_2_1_19_1","unstructured":"Henri J. Nussbaumer. 1982. The Fast Fourier Transform. Springer Berlin Heidelberg, 80\u2013111."},{"key":"e_1_3_2_1_20_1","unstructured":"Aaron van den Oord Yazhe Li and Oriol Vinyals. 2019. Representation Learning with Contrastive Predictive Coding."},{"key":"e_1_3_2_1_21_1","volume-title":"Gavneet Singh Chadha, and Andreas Schwung","author":"P\u00f6ppelbaum Johannes","year":"2022","unstructured":"Johannes P\u00f6ppelbaum, Gavneet Singh Chadha, and Andreas Schwung. 2022. Contrastive learning based self-supervised time-series analysis. Appl. Soft Comput. 117, C (March 2022), 14 pages."},{"key":"e_1_3_2_1_22_1","first-page":"3","article-title":"Traffic forecasting on new roads using spatial contrastive pre-training\u00a0(SCPT)","volume":"38","author":"Prabowo Arian","year":"2023","unstructured":"Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz, and Flora D. Salim. 2023. Traffic forecasting on new roads using spatial contrastive pre-training\u00a0(SCPT). Data Min. Knowl. Discov. 38, 3 (Sept. 2023), 913\u2013937.","journal-title":"Data Min. Knowl. Discov."},{"volume-title":"Introduction to graph theory","author":"West Douglas Brent","key":"e_1_3_2_1_23_1","unstructured":"Douglas Brent West and others. 2001. Introduction to graph theory. Vol. 2. Prentice hall Upper Saddle River."},{"key":"e_1_3_2_1_24_1","unstructured":"Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar and Steven Hoi. 2022. CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting."},{"key":"e_1_3_2_1_25_1","volume-title":"IJCAI'19","author":"Wu Zonghan","year":"1907","unstructured":"Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, and Chengqi Zhang. 2019. Graph wavenet for deep spatial-temporal graph modeling. In IJCAI'19. AAAI Press, 1907\u20131913."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3318984"}],"event":{"name":"SAC '25: 40th ACM\/SIGAPP Symposium on Applied Computing","sponsor":["SIGAPP ACM Special Interest Group on Applied Computing"],"location":"Catania International Airport Catania Italy","acronym":"SAC '25"},"container-title":["Proceedings of the 40th ACM\/SIGAPP Symposium on Applied Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3672608.3707852","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3672608.3707852","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:57:33Z","timestamp":1750298253000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3672608.3707852"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,31]]},"references-count":26,"alternative-id":["10.1145\/3672608.3707852","10.1145\/3672608"],"URL":"https:\/\/doi.org\/10.1145\/3672608.3707852","relation":{},"subject":[],"published":{"date-parts":[[2025,3,31]]},"assertion":[{"value":"2025-05-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}