{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T20:21:33Z","timestamp":1774729293725,"version":"3.50.1"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602097"],"award-info":[{"award-number":["61602097"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61472064"],"award-info":[{"award-number":["61472064"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["1213038"],"award-info":[{"award-number":["1213038"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000144","name":"Division of Computer and Network Systems","doi-asserted-by":"publisher","award":["1646107"],"award-info":[{"award-number":["1646107"]}],"id":[{"id":"10.13039\/100000144","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1109\/tnnls.2020.3005325","type":"journal-article","created":{"date-parts":[[2020,8,12]],"date-time":"2020-08-12T20:33:58Z","timestamp":1597264438000},"page":"2401-2414","source":"Crossref","is-referenced-by-count":16,"title":["Toward Discriminating and Synthesizing Motion Traces Using Deep Probabilistic Generative Models"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-8150","authenticated-orcid":false,"given":"Fan","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Xin","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1474-3169","authenticated-orcid":false,"given":"Kunpeng","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8839-6278","authenticated-orcid":false,"given":"Goce","family":"Trajcevski","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"4114","article-title":"Challenging common assumptions in the unsupervised learning of disentangled representations","author":"locatello","year":"2019","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref38","first-page":"1214","article-title":"Vae with a vampprior","author":"tomczak","year":"2018","journal-title":"Proc Int Conf Artif Intell Statist (AISTATS)"},{"key":"ref33","article-title":"Language GANs falling short","author":"caccia","year":"2018","journal-title":"arXiv 1811 02549"},{"key":"ref32","first-page":"5767","article-title":"Improved training of wasserstein gans","author":"gulrajani","year":"2017","journal-title":"Proc Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/530"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.39"},{"key":"ref37","first-page":"2","article-title":"Elbo surgery: Yet another way to carve up the evidence lower bound","author":"hoffman","year":"2016","journal-title":"Proc Workshop Adv Approx Bayesian Inference"},{"key":"ref36","first-page":"3581","article-title":"Semi-supervised learning with deep generative models","author":"kingma","year":"2014","journal-title":"Proc Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052620"},{"key":"ref34","article-title":"Efficient estimation of word representations in vector space","author":"mikolov","year":"2013","journal-title":"arXiv 1301 3781 [cs]"},{"key":"ref60","first-page":"2618","article-title":"Deeptransport: Prediction and simulation of human mobility and transportation mode at a citywide level","author":"song","year":"2016","journal-title":"Proc Int Joint Conf Artif Intell (IJCAI)"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.29012\/jpc.v7i3.405"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2855136"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref28","first-page":"5925","article-title":"Learning disentangled representations with semi-supervised deep generative models","author":"narayanaswamy","year":"2017","journal-title":"Proc Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref64","first-page":"6053","article-title":"Learning structured representation for text classification via reinforcement learning","author":"zhang","year":"2018","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref27","first-page":"1","article-title":"Deep unsupervised clustering with Gaussian mixture variational autoencoders","author":"dilokthanakul","year":"2017","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref66","article-title":"Dilated convolutions for modeling long-distance genomic dependencies","author":"gupta","year":"2017","journal-title":"arXiv 1710 01278"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.14778\/3055540.3055542"},{"key":"ref67","first-page":"1530","article-title":"Variational inference with normalizing flows","author":"rezende","year":"2015","journal-title":"Proc ICML"},{"key":"ref2","first-page":"194","article-title":"Predicting the next location: A recurrent model with spatial and temporal contexts","author":"liu","year":"2016","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098094"},{"key":"ref20","first-page":"1","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"2014","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref22","first-page":"3358","article-title":"Variational autoencoder for semi-supervised text classification","author":"xu","year":"2017","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref21","first-page":"2525","article-title":"Structured disentangled representations","author":"esmaeili","year":"2019","journal-title":"Proc 22nd Int Conf Artif Intell Statist"},{"key":"ref24","first-page":"1","article-title":"Beta-vae: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"2017","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2900734"},{"key":"ref26","first-page":"159","article-title":"Fixing a broken elbo","author":"alemi","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/K16-1002"},{"key":"ref50","article-title":"Stable recurrent models","author":"miller","year":"2018","journal-title":"arXiv 1805 10369"},{"key":"ref51","first-page":"1","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2015","journal-title":"Int Conf Learn Represent (ICLR)"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2695438"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2004.1357026"},{"key":"ref57","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"arXiv 1810 04805"},{"key":"ref56","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref55","first-page":"2610","article-title":"Isolating sources of disentanglement in variational autoencoders","author":"chen","year":"2018","journal-title":"Proc Conf Neural Inf Process Syst (NeurIPS)"},{"key":"ref54","first-page":"1","article-title":"Variational lossy autoencoder","author":"chen","year":"2017","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref53","first-page":"1","article-title":"Preventing posterior collapse with delta-vaes","author":"razavi","year":"2019","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2017-232"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref11","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"chung","year":"2014","journal-title":"arXiv 1412 3555"},{"key":"ref40","first-page":"1","article-title":"Weakly supervised disentanglement with guarantees","author":"shu","year":"2020","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186058"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210042"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313609"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2838320"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2924576"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2903448"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MDM.2016.47"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983672"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3274895.3274908"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313610"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/446"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/234"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623638"},{"key":"ref7","first-page":"2605","article-title":"Where you like to go next: Successive point-of-interest recommendation","author":"cheng","year":"2013","journal-title":"Proc Int Joint Conf Artif Intell (IJCAI)"},{"key":"ref49","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"bai","year":"2018","journal-title":"arXiv 1803 01271"},{"key":"ref9","first-page":"2117","article-title":"Learning User&#x2019;s intrinsic and extrinsic interests for point-of-interest recommendation: A unified approach","author":"li","year":"2017","journal-title":"Proc 26th Int Joint Conf Artif Intell"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3133036"},{"key":"ref45","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"ester","year":"1996","journal-title":"Proc KDD"},{"key":"ref48","first-page":"1243","article-title":"Convolutional sequence to sequence learning","author":"gehring","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3041658"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9939-00-05371-5"},{"key":"ref41","first-page":"1","article-title":"Disentangling factors of variation using few labels","author":"locatello","year":"2019","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.14778\/3115404.3115407"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/2661829.2661983"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/5962385\/9445711\/9165954-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9445711\/09165954.pdf?arnumber=9165954","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:53:15Z","timestamp":1652194395000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9165954\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6]]},"references-count":67,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2020.3005325","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6]]}}}