{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:05:40Z","timestamp":1777655140195,"version":"3.51.4"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/V006134\/1"],"award-info":[{"award-number":["EP\/V006134\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/V006177\/1"],"award-info":[{"award-number":["EP\/V006177\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/T007346\/1"],"award-info":[{"award-number":["EP\/T007346\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/L016508\/01"],"award-info":[{"award-number":["EP\/L016508\/01"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000287","name":"Royal Academy of Engineering","doi-asserted-by":"publisher","award":["RF201617\/16\/31"],"award-info":[{"award-number":["RF201617\/16\/31"]}],"id":[{"id":"10.13039\/501100000287","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000275","name":"Leverhulme Trust","doi-asserted-by":"publisher","award":["RF\/2020-310"],"award-info":[{"award-number":["RF\/2020-310"]}],"id":[{"id":"10.13039\/501100000275","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/lsp.2024.3361806","type":"journal-article","created":{"date-parts":[[2024,2,2]],"date-time":"2024-02-02T18:46:05Z","timestamp":1706899565000},"page":"631-635","source":"Crossref","is-referenced-by-count":1,"title":["Empirical Bayesian Imaging With Large-Scale Push-Forward Generative Priors"],"prefix":"10.1109","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4772-9527","authenticated-orcid":false,"given":"S.","family":"Melidonis","sequence":"first","affiliation":[{"name":"School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Holden","sequence":"additional","affiliation":[{"name":"School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3177-9884","authenticated-orcid":false,"given":"Y.","family":"Altmann","sequence":"additional","affiliation":[{"name":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6438-6772","authenticated-orcid":false,"given":"M.","family":"Pereyra","sequence":"additional","affiliation":[{"name":"School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3860-9167","authenticated-orcid":false,"given":"K. C.","family":"Zygalakis","sequence":"additional","affiliation":[{"name":"School of Mathematics, University of Edinburgh, Edinburgh, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1137\/17M1135694"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2047910"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2053941"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2869727"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/b138659"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00757"},{"key":"ref8","first-page":"8507","article-title":"Adversarial regularizers in inverse problems","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Lunz","year":"2018"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.627"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00984"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/GlobalSIP.2013.6737048"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2018.2880326"},{"key":"ref13","first-page":"5546","article-title":"Plug-and-play methods provably converge with properly trained denoisers","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ryu","year":"2019"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00129"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3261988"},{"key":"ref16","first-page":"537","article-title":"Compressed sensing using generative models","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Bora","year":"2017"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1137\/21M140225X"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1137\/21M1406313"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00251"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747128"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1137\/22M1496542"},{"key":"ref22","first-page":"1","article-title":"Large scale GAN training for high fidelity natural image synthesis","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Brock","year":"2018"},{"key":"ref23","first-page":"1","article-title":"Learning multi-scale local conditional probability models of images","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Kadkhodaie","year":"2023"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1002\/2017WR022148"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02093"},{"key":"ref26","first-page":"1530","article-title":"Variational inference with normalizing flows","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Rezende","year":"2015"},{"key":"ref27","first-page":"10215","article-title":"Glow: Generative flow with invertible 1x1 convolutions","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Kingma","year":"2018"},{"key":"ref28","first-page":"2722","article-title":"Flow++: Improving flow-based generative models with variational dequantization and architecture design","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ho","year":"2019"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2020.2986321"},{"key":"ref30","article-title":"Conditional generative adversarial nets","author":"Mirza","year":"2014"},{"key":"ref31","first-page":"1","article-title":"Why are conditional generative models better than unconditional ones?","volume-title":"Proc. NeurIPS Workshop Score-Based Methods","author":"Bao","year":"2022"},{"key":"ref32","first-page":"2421","article-title":"Intermediate layer optimization for inverse problems using deep generative models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Daras","year":"2021"},{"key":"ref33","first-page":"1","article-title":"Diffusion posterior sampling for general noisy inverse problems","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Chung","year":"2023"},{"key":"ref34","first-page":"23593","article-title":"Denoising diffusion restoration models","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Kawar","year":"2022"},{"key":"ref35","article-title":"Monte Carlo guided diffusion for Bayesian linear inverse problems","author":"Cardoso","year":"2023"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58558-7_42"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00404"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-9569-8_10"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-020-09986-y"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-010-9182-3"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1137\/21M1406349"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00194"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3045810"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref47","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Dhariwal","year":"2021"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1137\/20M1387961"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1137\/19M1283719"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1137\/22M1502240"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/97\/10380231\/10419008.pdf?arnumber=10419008","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T04:31:42Z","timestamp":1710390702000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10419008\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/lsp.2024.3361806","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}