{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:55:31Z","timestamp":1777492531363,"version":"3.51.4"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"DNB ASA through the funding of this research project"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3356913","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T18:43:52Z","timestamp":1705949032000},"page":"13213-13232","source":"Crossref","is-referenced-by-count":14,"title":["CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1977-9280","authenticated-orcid":false,"given":"Abdallah","family":"Alshantti","sequence":"first","affiliation":[{"name":"Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4310-7938","authenticated-orcid":false,"given":"Damiano","family":"Varagnolo","sequence":"additional","affiliation":[{"name":"Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2690-983X","authenticated-orcid":false,"given":"Adil","family":"Rasheed","sequence":"additional","affiliation":[{"name":"Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway"}]},{"given":"Aria","family":"Rahmati","sequence":"additional","affiliation":[{"name":"Sopra Steria, Oslo, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8180-0389","authenticated-orcid":false,"given":"Frank","family":"Westad","sequence":"additional","affiliation":[{"name":"Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocx079"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1108\/jmlc-10-2019-0081"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.5040\/9781782258674.0010"},{"key":"ref4","first-page":"1","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/mci.2018.2840738"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30490-4_56"},{"key":"ref7","article-title":"Conditional generative adversarial nets","author":"Mirza","year":"2014","journal-title":"arXiv:1411.1784"},{"key":"ref8","article-title":"Adversarial autoencoders","author":"Makhzani","year":"2015","journal-title":"arXiv:1511.05644"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2022.05.023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3383455.3422554"},{"key":"ref11","first-page":"2642","article-title":"Conditional image synthesis with auxiliary classifier GANs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Odena"},{"key":"ref12","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arjovsky"},{"key":"ref13","first-page":"1","article-title":"Improved training of Wasserstein GANs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Gulrajani"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/sp.2017.41"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/csf.2018.00027"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-79228-4_1"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2019-0008"},{"key":"ref18","article-title":"Differentially private generative adversarial network","author":"Xie","year":"2018","journal-title":"arXiv:1802.06739"},{"key":"ref19","first-page":"1","article-title":"PATE-GAN: Generating synthetic data with differential privacy guarantees","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Jordon"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467445"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3134428"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-020-00977-1"},{"issue":"3","key":"ref23","first-page":"441","article-title":"Using cart to generate partially synthetic public use microdata","volume":"21","author":"Reiter","year":"2005","journal-title":"J. Off. Statist."},{"key":"ref24","first-page":"5357","article-title":"Adversarial random forests for density estimation and generative modeling","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Watson"},{"key":"ref25","article-title":"Auto-encoding variational Bayes","author":"Kingma","year":"2013","journal-title":"arXiv:1312.6114"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ssci.2017.8285168"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2020.105950"},{"key":"ref28","first-page":"1","article-title":"Modeling tabular data using conditional GAN","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Xu"},{"key":"ref29","first-page":"1","article-title":"beta-VAE: Learning basic visual concepts with a constrained variational framework","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Higgins"},{"key":"ref30","first-page":"4263","article-title":"Invertible tabular GANs: Killing two birds with one stone for tabular data synthesis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Lee"},{"key":"ref31","article-title":"Copula flows for synthetic data generation","author":"Kamthe","year":"2021","journal-title":"arXiv:2101.00598"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20697"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.14778\/3231751.3231757"},{"key":"ref34","first-page":"286","article-title":"Generating multi-label discrete patient records using generative adversarial networks","volume-title":"Proc. Mach. Learn. Healthcare Conf.","author":"Choi"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114582"},{"key":"ref36","first-page":"97","article-title":"CTAB-GAN: Effective table data synthesizing","volume-title":"Proc. 13th Asian Conf. Mach. Learn.","volume":"157","author":"Zhao"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2905015"},{"key":"ref38","article-title":"Synthesizing tabular data using generative adversarial networks","author":"Xu","year":"2018","journal-title":"arXiv:1811.11264"},{"key":"ref39","first-page":"1","article-title":"VEEGAN: Reducing mode collapse in GANs using implicit variational learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Srivastava"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3390\/make5010019"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449999"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.2994762"},{"key":"ref43","first-page":"3146","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Ke"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1214\/06-ba104"},{"key":"ref45","first-page":"1","article-title":"Improved techniques for training GANs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Salimans"},{"key":"ref46","article-title":"Layer normalization","author":"Ba","year":"2016","journal-title":"arXiv:1607.06450"},{"key":"ref47","volume-title":"Adult Data Set","author":"Kohavi","year":"1996"},{"key":"ref48","volume-title":"Bank Marketing Data Set","author":"Moro","year":"2012"},{"key":"ref49","volume-title":"Default of Credit Card Clients Data Set","author":"Yeh","year":"2016"},{"key":"ref50","volume-title":"Diabetes Health Indicators Dataset","author":"Taboul","year":"2021"},{"key":"ref51","volume-title":"House Sales in King County, USA","year":"2021"},{"key":"ref52","volume-title":"Used Cars Auction Prices","author":"Tunguz","year":"2021"},{"key":"ref53","volume-title":"Handbook of Methods of Applied Statistics","author":"Chakravarti","year":"1967"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-92238-2_46"},{"key":"ref55","article-title":"NIPS 2016 tutorial: Generative adversarial networks","author":"Goodfellow","year":"2017","journal-title":"arXiv:1701.00160"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10410850.pdf?arnumber=10410850","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T12:59:32Z","timestamp":1706792372000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10410850\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":55,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3356913","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}