{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T10:00:44Z","timestamp":1775815244705,"version":"3.50.1"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korea Government","award":["2019-0-00079"],"award-info":[{"award-number":["2019-0-00079"]}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea (NRF) Grant Funded by the Korea Government","doi-asserted-by":"publisher","award":["2019R1A2C1006543"],"award-info":[{"award-number":["2019R1A2C1006543"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/tcyb.2021.3053599","type":"journal-article","created":{"date-parts":[[2021,3,4]],"date-time":"2021-03-04T20:45:39Z","timestamp":1614890739000},"page":"9684-9694","source":"Crossref","is-referenced-by-count":56,"title":["Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series"],"prefix":"10.1109","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2449-6488","authenticated-orcid":false,"given":"Ahmad Wisnu","family":"Mulyadi","sequence":"first","affiliation":[{"name":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3121-7734","authenticated-orcid":false,"given":"Eunji","family":"Jun","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7019-8962","authenticated-orcid":false,"given":"Heung-Il","family":"Suk","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.49"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3127881"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.13063\/2327-9214.1035"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1142\/9789813207813_0021"},{"key":"ref5","first-page":"253","article-title":"Directly modeling missing data in sequences with RNNs: Improved classification of clinical time series","volume-title":"Proc. 1st Mach. Learn. Healthcare Conf.","author":"Lipton"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-24271-9"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1177\/096228029600500302"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/9781119013563"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17103-1_60"},{"key":"ref10","article-title":"Auto-encoding variational bayes","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kingma"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107501"},{"key":"ref13","first-page":"1596","article-title":"Multivariate time series imputation with generative adversarial networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Luo"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852132"},{"key":"ref15","first-page":"6775","article-title":"BRITS: Bidirectional recurrent imputation for time series","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Cao"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2906426"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCOUTCOMES.109.875658"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2010-621"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/17.6.520"},{"key":"ref21","first-page":"1089","article-title":"Bayesian exponential family PCA","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Mohamed"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517\u20136161.1977.tb01600.x"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2923434"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4067"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/mpr.329"},{"key":"ref26","volume-title":"GP-VAE: Deep probabilistic time series imputation","author":"Fortuin","year":"2019"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2863020"},{"key":"ref28","article-title":"Multi-directional recurrent neural networks: A novel method for estimating missing data","volume-title":"Proc. Int. Conf. Mach. Learn. Time Series Workshop","author":"Yoon"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolmodel.2018.07.002"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/d14-1179"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1161\/01.CTR.101.23.e215"},{"key":"ref34","first-page":"245","article-title":"Predicting in-hospital mortality of ICU patients: The physionet\/computing in cardiology challenge 2012","volume-title":"Proc. Conf. Comput. Cardiol.","volume":"39","author":"Silva"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.35"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2018.04.007"},{"key":"ref37","first-page":"2980","article-title":"A recurrent latent variable model for sequential data","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chung"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2017.10.011"},{"key":"ref39","volume-title":"Innvestigate neural networks!","author":"Alber","year":"2018"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/9861400\/09370004.pdf?arnumber=9370004","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:51:57Z","timestamp":1704844317000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9370004\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":39,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2021.3053599","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}