{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T01:37:07Z","timestamp":1772933827758,"version":"3.50.1"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,8]]},"DOI":"10.1109\/bigdata66926.2025.11400982","type":"proceedings-article","created":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:57:57Z","timestamp":1772830677000},"page":"2934-2942","source":"Crossref","is-referenced-by-count":0,"title":["ImpuGAN: Learning Conditional Generative Models for Robust Data Imputation"],"prefix":"10.1109","author":[{"given":"Zalish","family":"Mahmud","sequence":"first","affiliation":[{"name":"The University of Texas at El Paso,Computer Science,El Paso,US"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anantaa","family":"Kotal","sequence":"additional","affiliation":[{"name":"The University of Texas at El Paso,Computer Science,El Paso,US"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aritran","family":"Piplai","sequence":"additional","affiliation":[{"name":"The University of Texas at El Paso,Computer Science,El Paso,US"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2307\/2984875"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v045.i03"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/17.6.520"},{"key":"ref4","first-page":"5689","article-title":"GAIN: Missing data imputation using generative adversarial nets","volume-title":"Proceedings of the 35th International Conference on Machine Learning","volume":"80","author":"Yoon","year":"10-15 Jul 2018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/63.3.581"},{"key":"ref6","doi-asserted-by":"crossref","DOI":"10.1002\/9781119013563","volume-title":"Statistical Analysis with Missing Data","author":"Little","year":"2002"},{"issue":"16","key":"ref7","first-page":"3057","article-title":"Multiple imputation in practice: a comparison of software packages","volume":"26","author":"Van Buuren","year":"2007","journal-title":"Statistics in Medicine"},{"key":"ref8","doi-asserted-by":"crossref","DOI":"10.1201\/9780429492259","volume-title":"Flexible imputation of missing data","author":"Van Buuren","year":"2018"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1111\/j.1751-5823.2010.00103.x"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr597"},{"key":"ref11","first-page":"2287","article-title":"Spectral regularization algorithms for learning large incomplete matrices","volume":"11","author":"Mazumder","year":"2010","journal-title":"Journal of Machine Learning Research"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s10208-009-9045-5"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"issue":"12","key":"ref14","article-title":"Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion","volume":"11","author":"Vincent","year":"2010","journal-title":"Journal of machine learning research"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93040-4_21"},{"key":"ref16","author":"Kingma","year":"2014","journal-title":"Auto-encoding variational bayes"},{"key":"ref17","article-title":"Miwae: Deep generative modelling and imputation of incomplete data sets","volume-title":"International Conference on Machine Learning","author":"Mattei","year":"2019"},{"key":"ref18","article-title":"Variational autoencoder with arbitrary conditioning","volume-title":"International Conference on Learning Representations (ICLR)","author":"Ivanov","year":"2019"},{"key":"ref19","first-page":"1651","article-title":"Gp-vae: Deep probabilistic time series imputation","volume-title":"International Conference on Artificial Intelligence and Statistics (AISTATS)","author":"Fortuin","year":"2020"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-24271-9"},{"key":"ref21","article-title":"Brits: Bidirectional recurrent imputation for time series","author":"Cao","year":"2018","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"119619","DOI":"10.1016\/j.eswa.2023.119619","article-title":"Saits: Self-attention-based imputation for time series","volume":"219","author":"Du","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref24","first-page":"5767","article-title":"Improved training of wasserstein gans","author":"Gulrajani","year":"2017","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/jsait.2020.2983071"},{"key":"ref26","author":"Mirza","year":"2014","journal-title":"Conditional generative adversarial nets"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BigData62323.2024.10826047"},{"key":"ref28","article-title":"Modeling tabular data using conditional gan","volume":"32","author":"Xu","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3510548.3519377"},{"key":"ref30","article-title":"Misgan: Learning from incomplete data with generative adversarial networks","volume-title":"7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6\u20139","author":"Li","year":"2019"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref32","first-page":"5508","article-title":"Time-series generative adversarial networks","author":"Yoon","year":"2019","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref33","article-title":"Adult dataset","volume-title":"UCI Machine Learning Repository","author":"Becker","year":"1996"},{"key":"ref34","article-title":"Pima indians diabetes database","volume-title":"N. I. of Diabetes, Digestive, and K. Diseases","year":"2016"},{"key":"ref35","article-title":"Heart Disease","volume-title":"UCI Machine Learning Repository","author":"MJanosi","year":"1989"}],"event":{"name":"2025 IEEE International Conference on Big Data (BigData)","location":"Macau, China","start":{"date-parts":[[2025,12,8]]},"end":{"date-parts":[[2025,12,11]]}},"container-title":["2025 IEEE International Conference on Big Data (BigData)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11400704\/11400712\/11400982.pdf?arnumber=11400982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T06:52:55Z","timestamp":1772866375000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11400982\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,8]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/bigdata66926.2025.11400982","relation":{},"subject":[],"published":{"date-parts":[[2025,12,8]]}}}