{"id":"https://openalex.org/W3123399218","doi":"https://doi.org/10.1109/tsp.2021.3114985","title":"Unitary Approximate Message Passing for Sparse Bayesian Learning","display_name":"Unitary Approximate Message Passing for Sparse Bayesian Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3123399218","doi":"https://doi.org/10.1109/tsp.2021.3114985","mag":"3123399218"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2021.3114985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3114985","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2101.09954","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101916362","display_name":"Man Luo","orcid":"https://orcid.org/0009-0001-0067-2283"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Man Luo","raw_affiliation_strings":["University of Wollongong, 8691 Wollongong, New South Wales, Australia, (e-mail: ml857@uowmail.edu.au)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wollongong, 8691 Wollongong, New South Wales, Australia, (e-mail: ml857@uowmail.edu.au)","institution_ids":["https://openalex.org/I204824540"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047844850","display_name":"Qinghua Guo","orcid":"https://orcid.org/0000-0002-5180-7854"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Qinghua Guo","raw_affiliation_strings":["University of Wollongong, 8691 Wollongong, New South Wales, Australia, 2522 (e-mail: qguo@uow.edu.au)"],"raw_orcid":"https://orcid.org/0000-0002-5180-7854","affiliations":[{"raw_affiliation_string":"University of Wollongong, 8691 Wollongong, New South Wales, Australia, 2522 (e-mail: qguo@uow.edu.au)","institution_ids":["https://openalex.org/I204824540"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012672471","display_name":"Ming Jin","orcid":"https://orcid.org/0000-0002-9824-7647"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Jin","raw_affiliation_strings":["College of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang, China, 315211 (e-mail: jinming@nbu.edu.cn)"],"raw_orcid":"https://orcid.org/0000-0002-9824-7647","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang, China, 315211 (e-mail: jinming@nbu.edu.cn)","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005913897","display_name":"Yonina C. Eldar","orcid":"https://orcid.org/0000-0003-4358-5304"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]},{"id":"https://openalex.org/I53964585","display_name":"Weizmann Institute of Science","ror":"https://ror.org/0316ej306","country_code":"IL","type":"education","lineage":["https://openalex.org/I53964585"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yonina C. Eldar","raw_affiliation_strings":["Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel, 32000 (e-mail: yonina.eldar@weizmann.ac.il)"],"raw_orcid":"https://orcid.org/0000-0003-4358-5304","affiliations":[{"raw_affiliation_string":"Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel, 32000 (e-mail: yonina.eldar@weizmann.ac.il)","institution_ids":["https://openalex.org/I174306211","https://openalex.org/I53964585"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Defeng Huang","orcid":"https://orcid.org/0000-0002-1431-8859"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]},{"id":"https://openalex.org/I4210120128","display_name":"St David's Medical Center","ror":"https://ror.org/02v5mzt02","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210120128"]}],"countries":["AU","US"],"is_corresponding":false,"raw_author_name":"Defeng Huang","raw_affiliation_strings":["School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, Western Australia, Australia, 6009 (e-mail: david.huang@uwa.edu.au)","David"],"raw_orcid":"https://orcid.org/0000-0002-1431-8859","affiliations":[{"raw_affiliation_string":"School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, Western Australia, Australia, 6009 (e-mail: david.huang@uwa.edu.au)","institution_ids":["https://openalex.org/I177877127"]},{"raw_affiliation_string":"David","institution_ids":["https://openalex.org/I4210120128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101618127","display_name":"Xiangming Meng","orcid":"https://orcid.org/0000-0003-3454-9643"},"institutions":[{"id":"https://openalex.org/I4210109338","display_name":"University of Tokyo Hospital","ror":"https://ror.org/022cvpj02","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210109338"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiangming Meng","raw_affiliation_strings":["The University of Tokyo, 13143 Bunkyo-ku, Tokyo, Japan, (e-mail: meng@g.ecc.u-tokyo.ac.jp)"],"raw_orcid":"https://orcid.org/0000-0003-3454-9643","affiliations":[{"raw_affiliation_string":"The University of Tokyo, 13143 Bunkyo-ku, Tokyo, Japan, (e-mail: meng@g.ecc.u-tokyo.ac.jp)","institution_ids":["https://openalex.org/I74801974","https://openalex.org/I4210109338"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1783,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42771735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"69","issue":null,"first_page":"6023","last_page":"6039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/unitary-transformation","display_name":"Unitary transformation","score":0.77286297082901},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.73829185962677},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.6042044162750244},{"id":"https://openalex.org/keywords/unitary-state","display_name":"Unitary state","score":0.6025435924530029},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5728054046630859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5680075287818909},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5539280772209167},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5527960062026978},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5129070281982422},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4960866868495941},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.48886650800704956},{"id":"https://openalex.org/keywords/look-ahead","display_name":"Look-ahead","score":0.4744846820831299},{"id":"https://openalex.org/keywords/state-vector","display_name":"State vector","score":0.46912550926208496},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4624934494495392},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4596206247806549},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4392521381378174},{"id":"https://openalex.org/keywords/transformation-matrix","display_name":"Transformation matrix","score":0.42298218607902527},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3254152536392212},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11749881505966187},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.10871309041976929},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0730588436126709}],"concepts":[{"id":"https://openalex.org/C179371143","wikidata":"https://www.wikidata.org/wiki/Q2495534","display_name":"Unitary transformation","level":3,"score":0.77286297082901},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.73829185962677},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.6042044162750244},{"id":"https://openalex.org/C67820243","wikidata":"https://www.wikidata.org/wiki/Q179164","display_name":"Unitary state","level":2,"score":0.6025435924530029},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5728054046630859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680075287818909},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5539280772209167},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5527960062026978},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5129070281982422},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4960866868495941},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.48886650800704956},{"id":"https://openalex.org/C147297375","wikidata":"https://www.wikidata.org/wiki/Q6674930","display_name":"Look-ahead","level":2,"score":0.4744846820831299},{"id":"https://openalex.org/C2777798563","wikidata":"https://www.wikidata.org/wiki/Q7603916","display_name":"State vector","level":2,"score":0.46912550926208496},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4624934494495392},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4596206247806549},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4392521381378174},{"id":"https://openalex.org/C165443888","wikidata":"https://www.wikidata.org/wiki/Q1482183","display_name":"Transformation matrix","level":3,"score":0.42298218607902527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3254152536392212},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11749881505966187},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.10871309041976929},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0730588436126709},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/tsp.2021.3114985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3114985","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2101.09954","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.09954","pdf_url":"https://arxiv.org/pdf/2101.09954","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pure.atira.dk:publications/8a3e1829-a0f3-46e4-8b9a-ea286d331b53","is_oa":false,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/8a3e1829-a0f3-46e4-8b9a-ea286d331b53","pdf_url":null,"source":{"id":"https://openalex.org/S4306402523","display_name":"UWA Profiles and Research Repository (University of Western Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Luo , M , Guo , Q , Jin , M , Eldar , Y C , Huang , D D & Meng , X 2021 , ' Unitary Approximate Message Passing for Sparse Bayesian Learning ' , IEEE Transactions on Signal Processing , vol. 69 , pp. 6023-6039 . https://doi.org/10.1109/TSP.2021.3114985","raw_type":"article"},{"id":"pmh:oai:ro.uow.edu.au:test2021-4169","is_oa":false,"landing_page_url":"https://ro.uow.edu.au/test2021/3160","pdf_url":null,"source":{"id":"https://openalex.org/S4306400510","display_name":"Research Online (University of Wollongong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I204824540","host_organization_name":"University of Wollongong","host_organization_lineage":["https://openalex.org/I204824540"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Test Series for Scopus Harvesting 2021","raw_type":"text"},{"id":"doi:10.48550/arxiv.2101.09954","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2101.09954","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:3123399218","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2101.09954","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.09954","pdf_url":"https://arxiv.org/pdf/2101.09954","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3358537321","display_name":null,"funder_award_id":"DP190100786","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320330828","display_name":"QuantERA","ror":null},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W655473902","https://openalex.org/W1516111018","https://openalex.org/W1537414256","https://openalex.org/W1539800233","https://openalex.org/W1648445109","https://openalex.org/W1744464229","https://openalex.org/W1770500012","https://openalex.org/W1908709377","https://openalex.org/W1970847729","https://openalex.org/W1975660262","https://openalex.org/W1985761548","https://openalex.org/W2010221098","https://openalex.org/W2029299478","https://openalex.org/W2044762091","https://openalex.org/W2082029531","https://openalex.org/W2091710249","https://openalex.org/W2091990110","https://openalex.org/W2119862467","https://openalex.org/W2123023890","https://openalex.org/W2129638195","https://openalex.org/W2146000945","https://openalex.org/W2152279006","https://openalex.org/W2156358825","https://openalex.org/W2164031139","https://openalex.org/W2166670884","https://openalex.org/W2596873572","https://openalex.org/W2603333836","https://openalex.org/W2605217922","https://openalex.org/W2776751579","https://openalex.org/W2884333066","https://openalex.org/W2907401811","https://openalex.org/W2942034734","https://openalex.org/W2963072996","https://openalex.org/W2963206527","https://openalex.org/W2963285090","https://openalex.org/W2964047892","https://openalex.org/W2978819667","https://openalex.org/W2979594461","https://openalex.org/W3008148299","https://openalex.org/W3031056847","https://openalex.org/W3036959716","https://openalex.org/W3104255649","https://openalex.org/W3198389221","https://openalex.org/W4235713725","https://openalex.org/W4248709896","https://openalex.org/W4300263211","https://openalex.org/W6637759562","https://openalex.org/W6639821106","https://openalex.org/W6682671827","https://openalex.org/W6684667123"],"related_works":["https://openalex.org/W3203940756","https://openalex.org/W3113493273","https://openalex.org/W2907401811","https://openalex.org/W2914177635","https://openalex.org/W2792076496","https://openalex.org/W3036667406","https://openalex.org/W3165210976","https://openalex.org/W2783180185","https://openalex.org/W2563113662","https://openalex.org/W2746047470","https://openalex.org/W2091710249","https://openalex.org/W3163177387","https://openalex.org/W3129036490","https://openalex.org/W2790212948","https://openalex.org/W2155701806","https://openalex.org/W2539609037","https://openalex.org/W2986208109","https://openalex.org/W3038630073","https://openalex.org/W2953786734","https://openalex.org/W2397289812"],"abstract_inverted_index":{"Sparse":[0],"Bayesian":[1],"learning":[2],"(SBL)":[3],"can":[4],"be":[5],"implemented":[6],"with":[7,69],"low":[8],"complexity":[9],"based":[10,62],"on":[11,63],"the":[12,44,47,96],"approximate":[13],"message":[14],"passing":[15],"(AMP)":[16],"algorithm.":[17],"However,":[18],"it":[19],"does":[20],"not":[21],"work":[22],"well":[23],"for":[24,40],"a":[25,58,70],"generic":[26],"measurement":[27,76,80],"matrix,":[28],"which":[29],"may":[30],"cause":[31],"AMP":[32,36,68],"to":[33,42,90,105],"diverge.":[34],"Damped":[35],"has":[37],"been":[38],"used":[39],"SBL":[41,60,94],"alleviate":[43],"problem":[45],"at":[46],"cost":[48],"of":[49],"reducing":[50],"convergence":[51],"speed.":[52],"In":[53],"this":[54],"work,":[55],"we":[56],"propose":[57],"new":[59],"algorithm":[61],"structured":[64],"variational":[65],"inference,":[66],"leveraging":[67],"unitary":[71],"transformation":[72],"(UAMP).":[73],"Both":[74],"single":[75],"vector":[77,81],"and":[78,102],"multiple":[79],"problems":[82],"are":[83],"investigated.":[84],"It":[85],"is":[86,99],"shown":[87],"that,":[88],"compared":[89],"stateof-":[91],"the-art":[92],"AMP-based":[93],"algorithms,":[95],"proposed":[97],"UAMPSBL":[98],"more":[100],"robust":[101],"efficient,":[103],"leading":[104],"remarkably":[106],"better":[107],"performance.":[108]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}