{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T21:04:57Z","timestamp":1762376697616,"version":"3.37.3"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001381","name":"Singapore National Research Foundation","doi-asserted-by":"publisher","award":["R-252-000-A74-281"],"award-info":[{"award-number":["R-252-000-A74-281"]}],"id":[{"id":"10.13039\/501100001381","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":[[2020,5]]},"DOI":"10.1109\/jsait.2020.2980676","type":"journal-article","created":{"date-parts":[[2020,3,13]],"date-time":"2020-03-13T20:21:16Z","timestamp":1584130876000},"page":"292-303","source":"Crossref","is-referenced-by-count":11,"title":["Information-Theoretic Lower Bounds for Compressive Sensing With Generative Models"],"prefix":"10.1109","volume":"1","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0392-6648","authenticated-orcid":false,"given":"Zhaoqiang","family":"Liu","sequence":"first","affiliation":[]},{"given":"Jonathan","family":"Scarlett","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Elements of Information Theory","year":"2006","author":"cover","key":"ref33"},{"key":"ref32","first-page":"1517","article-title":"Benefits of depth in neural networks","author":"telgarsky","year":"2016","journal-title":"Proc Conf Learn Theory (COLT)"},{"journal-title":"Representation benefits of deep feedforward networks","year":"2015","author":"telgarsky","key":"ref31"},{"key":"ref30","article-title":"Understanding deep neural networks with rectified linear units","author":"arora","year":"2018","journal-title":"Proc Int Conf on Learning Rep"},{"key":"ref36","article-title":"Depth-width trade-offs for ReLU networks via Sharkovsky’s theorem","author":"chatziafratis","year":"2020","journal-title":"Proc Int Conf on Learning Rep"},{"journal-title":"The universal approximation power of finite-width deep ReLU networks","year":"2018","author":"perekrestenko","key":"ref35"},{"journal-title":"An introductory guide to Fano’s inequality with applications in statistical estimation","year":"2019","author":"scarlett","key":"ref34"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2012.2215837"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2012.08.010"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2016.2606605"},{"journal-title":"Generative Deep Learning Teaching Machines to Paint Write Compose and Play","year":"2019","author":"foster","key":"ref13"},{"key":"ref14","first-page":"537","article-title":"Compressed sensing using generative models","author":"bora","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2010.2040894"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462233"},{"journal-title":"Solving Inverse Problems via Auto-Encoders","year":"2019","author":"jalali","key":"ref17"},{"key":"ref18","first-page":"1222","article-title":"Modeling sparse deviations for compressed sensing using generative models","author":"dhar","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref19","first-page":"970","article-title":"Global guarantees for enforcing deep generative priors by empirical risk","author":"hand","year":"2018","journal-title":"Proc Conf Learn Theory (COLT)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2016.2605122"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2009.2016018"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2013.2253852"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2005.864420"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2634550"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2011.2161794"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2004.834793"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093\/imaiai\/iau005"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2013.2274513"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1017\/9781108627771"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2009.2032816"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-8176-4948-7"},{"key":"ref20","first-page":"6697","article-title":"On the statistical rate of nonlinear recovery in generative models with heavy-tailed data","author":"wei","year":"2019","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref22","article-title":"Deep decoder: Concise image representations from untrained non-convolutional networks","author":"heckel","year":"2019","journal-title":"Proc Int Conf on Learning Rep"},{"journal-title":"Compressed sensing with deep image prior and learned regularization","year":"2018","author":"van veen","key":"ref21"},{"journal-title":"Distance-based and continuum Fano inequalities with applications to statistical estimation","year":"2013","author":"duchi","key":"ref24"},{"journal-title":"Lower bounds for compressed sensing with generative models","year":"2019","author":"kamath","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2009.2034796"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2010.2059891"}],"container-title":["IEEE Journal on Selected Areas in Information Theory"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8700143\/8768428\/09035653.pdf?arnumber=9035653","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T13:17:32Z","timestamp":1651065452000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9035653\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5]]},"references-count":36,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/jsait.2020.2980676","relation":{},"ISSN":["2641-8770"],"issn-type":[{"type":"electronic","value":"2641-8770"}],"subject":[],"published":{"date-parts":[[2020,5]]}}}