{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:02:00Z","timestamp":1771700520864,"version":"3.50.1"},"reference-count":61,"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:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3433383","type":"journal-article","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T17:31:57Z","timestamp":1721928717000},"page":"102688-102701","source":"Crossref","is-referenced-by-count":6,"title":["A Hybrid Quantum-Classical Generative Adversarial Network for Near-Term Quantum Processors"],"prefix":"10.1109","volume":"12","author":[{"given":"Albha","family":"O\u2019Dwyer Boyle","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9970-3368","authenticated-orcid":false,"given":"Reza","family":"Nikandish","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature23474"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1080\/00107514.2014.964942"},{"key":"ref3","article-title":"Classification with quantum neural networks on near term processors","author":"Farhi","year":"2018","journal-title":"arXiv:1802.06002"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11128-014-0809-8"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-021-00084-1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-14454-2"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s42354-021-0335-7"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1147\/jrd.2018.2888987"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.74.145"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/nature23461"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/nature23675"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1038\/nature07127"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/BF02650179"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.1994.365700"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/237814.237866"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1992.0167"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.103.150502"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1038\/npjqi.2015.23"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.22331\/q-2018-08-06-79"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1666-5"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04725-x"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-32550-3"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-021-00348-9"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TQE.2021.3062494"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-022-00311-3"},{"key":"ref26","first-page":"1","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1103\/physreva.98.012324"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.121.040502"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03928-y"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06096-3"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2019.2937234"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03469-4"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.94.015004"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1038\/s41534-019-0223-2"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1002\/qute.202000003"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1038\/s41534-021-00503-1"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aav2761"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.128.220505"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1103\/physrevlett.127.120502"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.22331\/q-2020-08-31-314"},{"key":"ref41","article-title":"Meta-learning in neural networks: A survey","author":"Hospedales","year":"2020","journal-title":"arXiv:2004.05439"},{"key":"ref42","article-title":"Learning to learn with quantum neural networks via classical neural networks","author":"Verdon","year":"2019","journal-title":"arXiv:1907.05415"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-07090-4"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-27045-6"},{"key":"ref45","article-title":"A review of quantum neural networks: Methods, models, dilemma","author":"Zhao","year":"2021","journal-title":"arXiv:2109.01840"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.99.032331"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.98.032309"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.104.062443"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-21728-w"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.22331\/q-2019-12-09-214"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3390\/a12020034"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1103\/physreva.102.032420"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.122.040504"},{"key":"ref54","article-title":"Loading classical data into a quantum computer","author":"Cortese","year":"2018","journal-title":"arXiv:1803.01958"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-0980-2"},{"key":"ref56","article-title":"Quantum embeddings for machine learning","author":"Lloyd","year":"2020","journal-title":"arXiv:2001.03622"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611973075.37"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.101.032308"},{"key":"ref59","first-page":"2234","article-title":"Improved techniques for training gans","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Salimans"},{"key":"ref60","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arjovsky"},{"key":"ref61","article-title":"Unrolled generative adversarial networks","author":"Metz","year":"2016","journal-title":"arXiv:1611.02163"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10380310\/10609392.pdf?arnumber=10609392","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T05:25:01Z","timestamp":1722662701000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10609392\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":61,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3433383","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}