{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:55:33Z","timestamp":1775696133692,"version":"3.50.1"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","award":["W911NF-17-C-0099"],"award-info":[{"award-number":["W911NF-17-C-0099"]}],"id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000774","name":"Defense Threat Reduction Agency","doi-asserted-by":"publisher","award":["HDTRA1-18-1-0026"],"award-info":[{"award-number":["HDTRA1-18-1-0026"]}],"id":[{"id":"10.13039\/100000774","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"publisher","award":["W911NF-09-2-0053"],"award-info":[{"award-number":["W911NF-09-2-0053"]}],"id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"publisher","award":["W911NF-17-2-0196"],"award-info":[{"award-number":["W911NF-17-2-0196"]}],"id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NSF","award":["CPS 20-38817"],"award-info":[{"award-number":["CPS 20-38817"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2022,12,1]]},"DOI":"10.1109\/tpami.2021.3127323","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T23:27:54Z","timestamp":1637191674000},"page":"9285-9297","source":"Crossref","is-referenced-by-count":16,"title":["ControlVAE: Tuning, Analytical Properties, and Performance Analysis"],"prefix":"10.1109","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7627-5615","authenticated-orcid":false,"given":"Huajie","family":"Shao","sequence":"first","affiliation":[{"name":"Department of Computer Science, College of William and Mary, Williamsburg, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7227-8552","authenticated-orcid":false,"given":"Zhisheng","family":"Xiao","sequence":"additional","affiliation":[{"name":"Committee on Computational and Applied Mathematics, University of Chicago, Chicago, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4070-6345","authenticated-orcid":false,"given":"Shuochao","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4000-2783","authenticated-orcid":false,"given":"Dachun","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aston","family":"Zhang","sequence":"additional","affiliation":[{"name":"Amazon Web Services, Palo Alto, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengzhong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3085-1434","authenticated-orcid":false,"given":"Tianshi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinyang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3883-7220","authenticated-orcid":false,"given":"Tarek","family":"Abdelzaher","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"700","article-title":"Are GANs created equal? A large-scale study","author":"lucic","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref38","author":"fortin","year":"2000","journal-title":"Augmented Lagrangian Methods Applications to the Numerical Solution of Boundary-Value Problems"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/37.526915"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-12883-2_1"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01269"},{"key":"ref30","article-title":"Diagnosing and enhancing VAE models","author":"dai","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref37","article-title":"Switchboard-1 release 2-linguistic data consortium","author":"godfrey","year":"1997","journal-title":"SWITCHBOARD A User&#x2019;s Manual"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.21236\/ADA273556"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref34","article-title":"dSprites: Disentanglement testing sprites dataset","author":"matthey","year":"2017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref27","first-page":"2610","article-title":"Isolating sources of disentanglement in variational autoencoders","author":"chen","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1147\/rd.41.0066"},{"key":"ref2","first-page":"1278","article-title":"Stochastic backpropagation and approximate inference in deep generative models","author":"rezende","year":"2014","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref1","article-title":"Auto-encoding variational bayes","volume":"1050","author":"kingma","year":"2013","journal-title":"Stat"},{"key":"ref20","first-page":"612","article-title":"Constrained differential optimization","author":"platt","year":"1987","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref22","first-page":"8655","article-title":"ControlVAE: Controllable variational autoencoder","author":"shao","year":"2020","journal-title":"Proc 37th Int Conf Mach Learn"},{"key":"ref21","first-page":"9133","article-title":"Responsive safety in reinforcement learning by PID lagrangian methods","author":"stooke","year":"2020","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref24","first-page":"240","article-title":"Cyclical annealing schedule: A simple approach to mitigating KL vanishing","author":"liu","year":"2019","journal-title":"Proc NAACL-HLT"},{"key":"ref23","article-title":"Theory and evaluation metrics for learning disentangled representations","author":"do","year":"2020","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1002\/047166880X"},{"key":"ref25","author":"\u00e5str\u00f6m","year":"2006","journal-title":"Advanced PID Control ISA-Instrum Syst Autom Soc Res Triangle"},{"key":"ref50","first-page":"3881","article-title":"Improved variational autoencoders for text modeling using dilated convolutions","author":"yang","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-3027"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/K16-1002"},{"key":"ref11","first-page":"4414","article-title":"Unsupervised learning of disentangled representations from video","author":"denton","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref40","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref12","article-title":"Taming VAEs","author":"rezende","year":"2018"},{"key":"ref13","first-page":"2866","article-title":"Learning hierarchical priors in VAEs","author":"klushyn","year":"2019","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref14","article-title":"Fixing a broken ELBO","author":"alemi","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015885"},{"key":"ref16","article-title":"Understanding disentangling in beta-VAE","author":"burgess","year":"2018"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034828"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00091"},{"key":"ref19","article-title":"Variational discriminator bottleneck: Improving imitation learning, inverse RL, and GANs by constraining information flow","author":"peng","year":"2019","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref4","first-page":"700","article-title":"Unsupervised image-to-image translation networks","author":"liu","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_47"},{"key":"ref6","first-page":"166","article-title":"Topic-guided variational autoencoders for text generation","author":"wang","year":"2019","journal-title":"Proc Conf North Amer Chapter Assoc Comput Linguistics Human Lang Tech -Proc Conf"},{"key":"ref5","author":"zhang","year":"2021","journal-title":"Dive into Deep Learning"},{"key":"ref8","article-title":"Beta-VAE: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref7","first-page":"1587","article-title":"Toward controlled generation of text","author":"hu","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref49","article-title":"From variational to deterministic autoencoders","author":"ghosh","year":"2019","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref9","first-page":"2654","article-title":"Disentangling by factorising","author":"kim","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref46","article-title":"Dynamic beta-VAEs for quantifying biodiversity by clustering optically recorded insect signals","author":"rydhmer","year":"2021"},{"key":"ref45","article-title":"Generalized ELBO with constrained optimization, GECO","author":"rezende","year":"2018","journal-title":"Proc Workshop Bayesian Deep Learn NeurIPS"},{"key":"ref48","article-title":"Generative latent flow: A framework for non-adversarial image generation","author":"xiao","year":"2019"},{"key":"ref47","article-title":"Diagnosing and enhancing VAE models","author":"dai","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref42","article-title":"DP-GAN: Diversity-promoting generative adversarial network for generating informative and diversified text","author":"xu","year":"2018"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1061"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1121\/1.2016299"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210080"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/34\/9940446\/9618835-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/9940446\/09618835.pdf?arnumber=9618835","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T22:38:50Z","timestamp":1670279930000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9618835\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,1]]},"references-count":51,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2021.3127323","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,1]]}}}