{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T02:08:09Z","timestamp":1777342089733,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Institute of Information & Communications Technology Planning & Evaluation (IITP)","award":["2020-0-01361"],"award-info":[{"award-number":["2020-0-01361"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,26]]},"DOI":"10.1145\/3459637.3482449","type":"proceedings-article","created":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T18:33:14Z","timestamp":1635618794000},"page":"251-260","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":29,"title":["LT-OCF"],"prefix":"10.1145","author":[{"given":"Jeongwhan","family":"Choi","sequence":"first","affiliation":[{"name":"Yonsei University, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinsung","family":"Jeon","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noseong","family":"Park","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Context-Aware Recommender Systems","author":"Adomavicius Gediminas","unstructured":"Gediminas Adomavicius and Alexander Tuzhilin . 2015. Context-Aware Recommender Systems . Springer US , 191--226. Gediminas Adomavicius and Alexander Tuzhilin. 2015. Context-Aware Recommender Systems. Springer US, 191--226."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/3157096.3157320"},{"key":"e_1_3_2_2_3_1","unstructured":"Joan Bruna Wojciech Zaremba Arthur Szlam and Yann LeCun. 2014. Spectral networks and deep locally connected networks on graphs. In ICLR. 1--14. arXiv:1312.6203  Joan Bruna Wojciech Zaremba Arthur Szlam and Yann LeCun. 2014. Spectral networks and deep locally connected networks on graphs. In ICLR. 1--14. arXiv:1312.6203"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Deli Chen Yankai Lin Wei Li Peng Li Jie Zhou and Xu Sun. 2020. Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View. In AAAI.  Deli Chen Yankai Lin Wei Li Peng Li Jie Zhou and Xu Sun. 2020. Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View. In AAAI.","DOI":"10.1609\/aaai.v34i04.5747"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"crossref","unstructured":"Lei Chen Le Wu Richang Hong Kun Zhang and Meng Wang. 2020. Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI.  Lei Chen Le Wu Richang Hong Kun Zhang and Meng Wang. 2020. Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI.","DOI":"10.1609\/aaai.v34i01.5330"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2877208"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/3327757.3327764"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.5555\/3157382.3157527"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/0771-050X(80)90013-3"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3454569"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209991"},{"key":"e_1_3_2_2_12_1","volume-title":"Introduction to Partial Differential Equations","author":"GERALD B. FOLLAND.","unstructured":"GERALD B. FOLLAND. 1995. Introduction to Partial Differential Equations : Second Edition. Vol. 102 . Princeton University Press . GERALD B. FOLLAND. 1995. Introduction to Partial Differential Equations: Second Edition. Vol. 102. Princeton University Press."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219947"},{"key":"e_1_3_2_2_14_1","volume-title":"Dahl","author":"Gilmer Justin","year":"2017","unstructured":"Justin Gilmer , Samuel S. Schoenholz , Patrick F. Riley , Oriol Vinyals , and George E . Dahl . 2017 . Neural Message Passing for Quantum Chemistry. ICML 3 (apr 2017), 2053--2070. arXiv:1704.01212 Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl. 2017. Neural Message Passing for Quantum Chemistry. ICML 3 (apr 2017), 2053--2070. arXiv:1704.01212"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/3294771.3294869"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2831682"},{"key":"e_1_3_2_2_18_1","unstructured":"Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-seng Chua. 2017. Neural Collaborative Filtering. In WWW. 173--182.  Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-seng Chua. 2017. Neural Collaborative Filtering. In WWW. 173--182."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481935"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"crossref","unstructured":"Sheo Yon Jhin Minju Jo Taeyong Kong Jinsung Jeon and Noseong Park. 2021. ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations. In KDD.  Sheo Yon Jhin Minju Jo Taeyong Kong Jinsung Jeon and Noseong Park. 2021. ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations. In KDD.","DOI":"10.1145\/3447548.3467419"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449999"},{"key":"e_1_3_2_2_22_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. Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1644873.1644874"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_26_1","unstructured":"Gustav Larsson M. Maire and Gregory Shakhnarovich. 2017. FractalNet: UltraDeep Neural Networks without Residuals. In ICLR.  Gustav Larsson M. Maire and Gregory Shakhnarovich. 2017. FractalNet: UltraDeep Neural Networks without Residuals. In ICLR."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186150"},{"key":"e_1_3_2_2_28_1","unstructured":"Yiping Lu Aoxiao Zhong Quanzheng Li and Bin Dong. 2018. Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations. In ICML.  Yiping Lu Aoxiao Zhong Quanzheng Li and Bin Dong. 2018. Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations. In ICML."},{"key":"e_1_3_2_2_29_1","unstructured":"Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita and Hajime Asama. 2020. Dissecting Neural ODEs. arXiv:2002.08071 [cs.LG]  Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita and Hajime Asama. 2020. Dissecting Neural ODEs. arXiv:2002.08071 [cs.LG]"},{"key":"e_1_3_2_2_30_1","volume-title":"Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands. arXiv:1910.10470","author":"Pinckaers Hans","year":"2019","unstructured":"Hans Pinckaers and Geert Litjens . 2019. Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands. arXiv:1910.10470 ( 2019 ). Hans Pinckaers and Geert Litjens. 2019. Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands. arXiv:1910.10470 (2019)."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.5555\/2969442.2969475"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/1795114.1795167"},{"key":"e_1_3_2_2_33_1","volume-title":"Graph Convolutional Matrix Completion. CoRR abs\/1706.02263","author":"van den Berg Rianne","year":"2017","unstructured":"Rianne van den Berg , Thomas N. Kipf , and Max Welling . 2017. Graph Convolutional Matrix Completion. CoRR abs\/1706.02263 ( 2017 ). arXiv:1706.02263 Rianne van den Berg, Thomas N. Kipf, and Max Welling. 2017. Graph Convolutional Matrix Completion. CoRR abs\/1706.02263 (2017). arXiv:1706.02263"},{"key":"e_1_3_2_2_34_1","volume-title":"Graph Attention Networks. In ICLR","author":"Cucurull Guillem","year":"2017","unstructured":"Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Li\u00f2 , and Yoshua Bengio . 2017 . Graph Attention Networks. In ICLR 2018. 1--12. arXiv:1710.10903 Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2017. Graph Attention Networks. In ICLR 2018. 1--12. arXiv:1710.10903"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783273"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313417"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351034"},{"key":"e_1_3_2_2_39_1","volume-title":"Christopher Fifty, Tao Yu, and Kilian Q. Weinberger.","author":"Wu Felix","year":"2019","unstructured":"Felix Wu , Tianyi Zhang , Amauri Holanda de Souza , Christopher Fifty, Tao Yu, and Kilian Q. Weinberger. 2019 . Simplifying Graph Convolutional Networks. In ICML , Vol. 2019-June. 11884-- 11894 . arXiv:1902.07153 Felix Wu, Tianyi Zhang, Amauri Holanda de Souza, Christopher Fifty, Tao Yu, and Kilian Q. Weinberger. 2019. Simplifying Graph Convolutional Networks. In ICML, Vol. 2019-June. 11884--11894. arXiv:1902.07153"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2835776.2835837"},{"key":"e_1_3_2_2_41_1","unstructured":"Bingbing Xu Huawei Shen Qi Cao Yunqi Qiu and Xueqi Cheng. 2019. Graph Wavelet Neural Network. In ICLR. 1--13. arXiv:1904.07785  Bingbing Xu Huawei Shen Qi Cao Yunqi Qiu and Xueqi Cheng. 2019. Graph Wavelet Neural Network. In ICLR. 1--13. arXiv:1904.07785"},{"key":"e_1_3_2_2_42_1","unstructured":"Hanshu Yan Jiawei Du Vincent Y. F. Tan and Jiashi Feng. 2020. On Robustness of Neural Ordinary Differential Equations. arXiv:1910.05513  Hanshu Yan Jiawei Du Vincent Y. F. Tan and Jiashi Feng. 2020. On Robustness of Neural Ordinary Differential Equations. arXiv:1910.05513"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240381"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2016.2573314"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3285029"},{"key":"e_1_3_2_2_47_1","unstructured":"Mai Zhu Bo Chang and Chong Fu. 2019. Convolutional Neural Networks combined with Runge-Kutta Methods. arXiv:1802.08831  Mai Zhu Bo Chang and Chong Fu. 2019. Convolutional Neural Networks combined with Runge-Kutta Methods. arXiv:1802.08831"}],"event":{"name":"CIKM '21: The 30th ACM International Conference on Information and Knowledge Management","location":"Virtual Event Queensland Australia","acronym":"CIKM '21","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482449","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3459637.3482449","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:49Z","timestamp":1750193329000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482449"}},"subtitle":["Learnable-Time ODE-based Collaborative Filtering"],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":47,"alternative-id":["10.1145\/3459637.3482449","10.1145\/3459637"],"URL":"https:\/\/doi.org\/10.1145\/3459637.3482449","relation":{},"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"2021-10-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}