{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:17:57Z","timestamp":1776183477297,"version":"3.50.1"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","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":"am","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":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["DMS-2134037"],"award-info":[{"award-number":["DMS-2134037"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF CAREER Award","doi-asserted-by":"publisher","award":["CCF-1650913"],"award-info":[{"award-number":["CCF-1650913"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["DMS-2134037"],"award-info":[{"award-number":["DMS-2134037"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["CMMI-2015787"],"award-info":[{"award-number":["CMMI-2015787"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["DMS-1938106"],"award-info":[{"award-number":["DMS-1938106"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["DMS-1830210"],"award-info":[{"award-number":["DMS-1830210"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000879","name":"Alfred P. Sloan Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000879","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Areas Inf. Theory"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/jsait.2022.3221864","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T21:45:53Z","timestamp":1668462353000},"page":"454-467","source":"Crossref","is-referenced-by-count":7,"title":["Invertible Neural Networks for Graph Prediction"],"prefix":"10.1109","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6623-7084","authenticated-orcid":false,"given":"Chen","family":"Xu","sequence":"first","affiliation":[{"name":"School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuyuan","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6777-2951","authenticated-orcid":false,"given":"Yao","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.5772\/intechopen.85571"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-71278-5_27"},{"key":"ref3","first-page":"1","article-title":"Analyzing inverse problems with invertible neural networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Ardizzone"},{"key":"ref4","article-title":"Guided image generation with conditional invertible neural networks","volume-title":"arXiv:1907.02392","author":"Ardizzone","year":"2019"},{"key":"ref5","first-page":"573","article-title":"Invertible residual networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Behrmann"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s002110050002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2789985"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfa.2012.07.007"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2307\/2118564"},{"key":"ref10","first-page":"1","article-title":"Residual flows for invertible generative modeling","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Chen"},{"key":"ref11","first-page":"1","article-title":"Graph convolution with low-rank learnable local filters","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Cheng"},{"key":"ref12","first-page":"1","article-title":"Fast and accurate deep network learning by exponential linear units (elus)","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Clevert"},{"key":"ref13","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Defferrard"},{"key":"ref14","first-page":"1","article-title":"Density estimation using real NVP","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Dinh"},{"key":"ref15","first-page":"1","article-title":"Generative adversarial nets","volume-title":"Proc. NIPS","author":"Goodfellow"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-020-05929-w"},{"key":"ref17","first-page":"1","article-title":"Scalable reversible generative models with free-form continuous dynamics","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Grathwohl"},{"key":"ref18","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"Gretton","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref19","first-page":"1","article-title":"Improved training of wasserstein GANs","volume-title":"Proc. NIPS","author":"Gulrajani"},{"key":"ref20","article-title":"Bridging mean-field games and normalizing flows with trajectory regularization","volume-title":"arXiv:2206.14990","author":"Huang","year":"2022"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1137\/S0036141096303359"},{"key":"ref23","article-title":"Adam: A method for stochastic optimization","volume-title":"arXiv:1412.6980","author":"Kingma","year":"2015"},{"key":"ref24","article-title":"Auto-encoding variational bayes","volume-title":"arXiv:1312.6114","author":"Kingma","year":"2014"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1561\/2200000056"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2992934"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-0346-0332-4"},{"key":"ref29","first-page":"1","article-title":"Understanding posterior collapse in generative latent variable models","volume-title":"Proc. DGS ICLR","author":"Lucas"},{"key":"ref30","article-title":"Adversarial autoencoders","volume-title":"arXiv:1511.05644","author":"Makhzani","year":"2015"},{"key":"ref31","article-title":"Conditional generative adversarial nets","volume-title":"arXiv:1411.1784","author":"Mirza","year":"2014"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17113"},{"issue":"57","key":"ref33","first-page":"1","article-title":"Normalizing flows for probabilistic modeling and inference","volume":"22","author":"Papamakarios","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref34","article-title":"Improved techniques for training gans","volume":"29","author":"Salimans","year":"2016","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1126\/science.aat2663"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jspi.2013.03.018"},{"key":"ref37","volume-title":"Elements of Information Theory","author":"Thomas","year":"2006"},{"key":"ref38","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-71050-9","volume-title":"Optimal Transport: Old and New","volume":"338","author":"Villani","year":"2009"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1090\/gsm\/058"},{"key":"ref40","first-page":"1","article-title":"Unconstrained monotonic neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Wehenkel"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-03646-8"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.06.024"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref45","first-page":"1","article-title":"Deep autoencoding Gaussian mixture model for unsupervised anomaly detection","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zong"}],"container-title":["IEEE Journal on Selected Areas in Information Theory"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/8700143\/10077203\/9950057-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8700143\/10077203\/09950057.pdf?arnumber=9950057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T02:01:43Z","timestamp":1706752903000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9950057\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":45,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/jsait.2022.3221864","relation":{},"ISSN":["2641-8770"],"issn-type":[{"value":"2641-8770","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}