{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T12:39:28Z","timestamp":1774701568812,"version":"3.50.1"},"reference-count":58,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":["61872151"],"award-info":[{"award-number":["61872151"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2022A1515011755"],"award-info":[{"award-number":["2022A1515011755"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Singapore MOE Academic Research Fund","award":["R-146-000-315-114"],"award-info":[{"award-number":["R-146-000-315-114"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tsp.2022.3170710","type":"journal-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T19:41:51Z","timestamp":1651088511000},"page":"2239-2252","source":"Crossref","is-referenced-by-count":14,"title":["Unsupervised Phase Retrieval Using Deep Approximate MMSE Estimation"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1904-6688","authenticated-orcid":false,"given":"Mingqin","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Peikang","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2564-7703","authenticated-orcid":false,"given":"Yuhui","family":"Quan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Tongyao","family":"Pang","sequence":"additional","affiliation":[{"name":"Department of Mathematics, National University of Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1674-6056","authenticated-orcid":false,"given":"Hui","family":"Ji","sequence":"additional","affiliation":[{"name":"Department of Mathematics, National University of Singapore, Singapore"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3057261"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3067164"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2015.2448516"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2015.2399924"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-013-0738-9"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2013.2297687"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.2971192"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2018.2800768"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2684758"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1214\/16-AOS1443"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2021.3049172"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1364\/AO.21.002758"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1002\/cpa.21432"},{"key":"ref2","first-page":"231","author":"stark","year":"1987","journal-title":"Image Recovery Theory and Application"},{"key":"ref1","first-page":"237","article-title":"A practical algorithm for the determination of phase from image and diffraction plane pictures","volume":"35","author":"gerchberg","year":"1972","journal-title":"Optik"},{"key":"ref20","first-page":"9154","article-title":"Phase retrieval under a generative prior","author":"hand","year":"0","journal-title":"Proc NeurIPS"},{"key":"ref22","first-page":"14803","article-title":"Algorithmic guarantees for inverse imaging with untrained network priors","author":"jagatap","year":"0","journal-title":"Proc NeurIPS"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3018751"},{"key":"ref24","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01303-4"},{"key":"ref26","first-page":"5574","article-title":"What uncertainties do we need in bayesian deep learning for computer vision","author":"kendall","year":"0","journal-title":"Proc NeurIPS"},{"key":"ref25","article-title":"Bayesian convolutional neural networks with Bernoulli approximate variational inference","author":"gal","year":"0","journal-title":"Proc ICLR"},{"key":"ref50","first-page":"1","article-title":"Phase retrieval with holography and untrained priors: Tackling the challenges of low-photon nanoscale imaging","volume":"107","author":"lawrence","year":"0","journal-title":"Proc Mach Learn Representations"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1364\/COSI.2021.CTh5A.2"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICCPHOT.2017.7951483"},{"key":"ref57","first-page":"10158","article-title":"Tuning-free plug-and-play proximal algorithm for inverse imaging problems","author":"wei","year":"0","journal-title":"Proc ICML"},{"key":"ref56","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref55","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"0","journal-title":"Proc 13th Int Conf Artif Intell Statist JMLR Workshop Conf Proc"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007665907178"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"2628","DOI":"10.1609\/aaai.v35i3.16366","article-title":"Deep probabilistic imaging: Uncertainty quantification and multi-modal solution characterization for computational imaging","volume":"35","author":"sun","year":"0","journal-title":"Proc AAAI"},{"key":"ref52","article-title":"Deep decoder: Concise image representations from untrained non-convolutional networks","author":"heckel","year":"0","journal-title":"Proc ICLR"},{"key":"ref10","first-page":"2504","article-title":"BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising","author":"metzler","year":"0","journal-title":"Proc ICIP"},{"key":"ref40","first-page":"537","article-title":"Compressed sensing using generative models","author":"bora","year":"0","journal-title":"Proc ICML"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2745459"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2019.2931169"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1137\/16M1103270"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2018.04.010"},{"key":"ref15","article-title":"Phase retrieval from noisy data based on sparse approximation of object phase and amplitude","author":"katkovnik","year":"2017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1117\/1.OE.56.9.094103"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAB.35.001271"},{"key":"ref18","first-page":"3501","article-title":"prDeep: Robust phase retrieval with a flexible deep network","author":"metzler","year":"0","journal-title":"Proc ICML"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2019.107350"},{"key":"ref4","doi-asserted-by":"crossref","DOI":"10.1038\/lsa.2017.141","article-title":"Phase recovery and holographic image reconstruction using deep learning in neural networks","volume":"7","author":"rivenson","year":"2017","journal-title":"Light Sci Appl"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01038"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.7.000394"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2019.2948758"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58577-8_26"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.389314"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TASSP.1982.1163863"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2014.2386294"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.901238"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2176954"},{"key":"ref48","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"2015"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.300"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2607180"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2018.05.011"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.29.000105"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9413991"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/78\/9675017\/09764626.pdf?arnumber=9764626","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T20:01:03Z","timestamp":1675454463000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9764626\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":58,"URL":"https:\/\/doi.org\/10.1109\/tsp.2022.3170710","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"value":"1053-587X","type":"print"},{"value":"1941-0476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}