{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T16:28:14Z","timestamp":1782145694069,"version":"3.54.5"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Mag."],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1109\/msp.2022.3207451","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T18:55:44Z","timestamp":1672685744000},"page":"164-182","source":"Crossref","is-referenced-by-count":52,"title":["Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications"],"prefix":"10.1109","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7957-8758","authenticated-orcid":false,"given":"Subhadip","family":"Mukherjee","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Bath, Bath, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3756-8121","authenticated-orcid":false,"given":"Andreas","family":"Hauptmann","sequence":"additional","affiliation":[{"name":"Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1118-6483","authenticated-orcid":false,"given":"Ozan","family":"Oktem","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Uppsala University, Uppsala, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6438-6772","authenticated-orcid":false,"given":"Marcelo","family":"Pereyra","sequence":"additional","affiliation":[{"name":"Mathematical Sciences and the School of Mathematical and Computer Sciences, Heriot–Watt University, Edinburgh, Scotland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0099-6306","authenticated-orcid":false,"given":"Carola-Bibiane","family":"Schonlieb","sequence":"additional","affiliation":[{"name":"University of Cambridge, Cambridge, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1-sidebar2","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2022.3148324"},{"key":"ref2-sidebar2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1907377117"},{"key":"ref3-sidebar2","doi-asserted-by":"publisher","DOI":"10.1137\/22m1503221"},{"key":"ref1","volume-title":"Variational Methods in Imaging","author":"Scherzer","year":"2009"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1017\/s0962492918000016"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1017\/s0962492919000059"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/msp.2017.2760358"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/b138659"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1137\/18m1174076"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2011.00771.x"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/tit.2006.871582"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/msp.2007.914731"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1515\/9783110208276"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1088\/0266-5611\/22\/1\/010"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1137\/20m1338460"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2117203119"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/tip.2017.2713099"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1137\/17m1141771"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2018.2799231"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26977"},{"key":"ref18","first-page":"537","article-title":"Compressed sensing using generative models","volume-title":"Proc. 34th Int. Conf. Mach. Learn. Res.","volume":"70","author":"Bora","year":"2017"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6420\/ab6d57"},{"key":"ref20","first-page":"8507","article-title":"Adversarial regularizers in inverse problems","volume-title":"Proc. 32nd Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Lunz","year":"2018"},{"key":"ref21","article-title":"Accelerated forward-backward optimization using deep learning","author":"Banert","year":"2021"},{"key":"ref22","first-page":"21,413","article-title":"End-to-end reconstruction meets data-driven regularization for inverse problems","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Mukherjee","year":"2021"},{"key":"ref23","article-title":"Learned convex regularizers for inverse problems","author":"Mukherjee","year":"2020"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1118\/1.4957556"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2016.2629286"},{"key":"ref26","article-title":"Gradient step denoiser for convergent plug-and-play","author":"Hurault","year":"2021"},{"key":"ref27","first-page":"146","article-title":"Input convex neural networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Amos","year":"2017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1088\/2399-6528\/ac26aa"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6420\/abc7cd"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1137\/21m1414978"},{"key":"ref31","first-page":"9446","article-title":"Deep image prior","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Ulyanov","year":"2018"},{"key":"ref32","first-page":"1","article-title":"Algorithmic guarantees for inverse imaging with untrained network priors","volume-title":"Proc. 33rd Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Jagatap","year":"2019"},{"key":"ref33","first-page":"1","article-title":"GAN-based projector for faster recovery in compressed sensing with convergence guarantees","volume-title":"Proc. 2019 IEEE\/CVF Int. Conf. Comput. Vis. (ICCV)","author":"Raj"},{"key":"ref34","first-page":"399","article-title":"Learning fast approximations of sparse coding","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gregor","year":"2010"},{"key":"ref35","article-title":"Deep Bayesian inversion","author":"Adler","year":"2018"},{"key":"ref36","first-page":"1","article-title":"Deep equilibrium models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Bai","year":"2019"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2021.3118944"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20619"},{"key":"ref39","first-page":"1","article-title":"SHINE: SHaring the INverse estimate from the forward pass for bi-level optimization and implicit models","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Ramzi","year":"2022"},{"key":"ref40","article-title":"Stochastic primal-dual deep unrolling","author":"Tang","year":"2021"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s00041-020-09761-7"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6420\/aaf14a"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/globalsip.2013.6737048"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2016.2599778"},{"key":"ref45","first-page":"5546","article-title":"Plug-and-play methods provably converge with properly trained denoisers","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","volume":"97","author":"Ryu","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2021.3066053"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/IEEECONF51394.2020.9443410"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1137\/20m1387961"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2018.2880326"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1137\/22m1508613"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-4314-2"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-4145-2"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1137\/19m1247176"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1088\/1742-5468\/ab321a"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/jsait.2020.2986321"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1137\/21m1406349"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s10851-022-01134-7"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1137\/21m1406313"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1137\/21m140225x"}],"container-title":["IEEE Signal Processing Magazine"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/79\/10004746\/10004773.pdf?arnumber=10004773","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,9]],"date-time":"2024-02-09T02:50:07Z","timestamp":1707447007000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10004773\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1]]},"references-count":62,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/msp.2022.3207451","relation":{},"ISSN":["1053-5888","1558-0792"],"issn-type":[{"value":"1053-5888","type":"print"},{"value":"1558-0792","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1]]}}}