{"id":"https://openalex.org/W4313524853","doi":"https://doi.org/10.1109/msp.2022.3208394","title":"Physics-Inspired Compressive Sensing: Beyond deep unrolling","display_name":"Physics-Inspired Compressive Sensing: Beyond deep unrolling","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313524853","doi":"https://doi.org/10.1109/msp.2022.3208394"},"language":"en","primary_location":{"id":"doi:10.1109/msp.2022.3208394","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msp.2022.3208394","pdf_url":null,"source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100409856","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0001-5486-3125"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["Assistant Professor, Peking University Shenzhen Graduate School, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Assistant Professor, Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427384","display_name":"Bin Chen","orcid":"https://orcid.org/0000-0002-9056-3717"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Chen","raw_affiliation_strings":["Computer Applications Technology, Peking University Shenzhen Graduate School, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Computer Applications Technology, Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013727612","display_name":"Ruiqin Xiong","orcid":"https://orcid.org/0000-0001-9796-0478"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiqin Xiong","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101653272","display_name":"Yongbing Zhang","orcid":"https://orcid.org/0009-0008-1568-3728"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongbing Zhang","raw_affiliation_strings":["Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100409856"],"corresponding_institution_ids":["https://openalex.org/I4210128628"],"apc_list":null,"apc_paid":null,"fwci":18.922,"has_fulltext":false,"cited_by_count":90,"citation_normalized_percentile":{"value":0.99835396,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"40","issue":"1","first_page":"58","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7009713649749756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6299179792404175},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6065286993980408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.535603940486908},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5070059299468994},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48311781883239746},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4473581910133362},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3788512945175171},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3679715394973755},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.16499638557434082}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7009713649749756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6299179792404175},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6065286993980408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.535603940486908},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5070059299468994},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48311781883239746},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4473581910133362},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3788512945175171},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3679715394973755},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.16499638557434082},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/msp.2022.3208394","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msp.2022.3208394","pdf_url":null,"source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2389558678","display_name":null,"funder_award_id":"62072009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5217273760","display_name":null,"funder_award_id":"62031023","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8533630715","display_name":null,"funder_award_id":"61902009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1996726072","https://openalex.org/W2018990310","https://openalex.org/W2082029531","https://openalex.org/W2119667497","https://openalex.org/W2122548617","https://openalex.org/W2130120519","https://openalex.org/W2273561594","https://openalex.org/W2552808051","https://openalex.org/W2773850766","https://openalex.org/W2798559986","https://openalex.org/W2922902233","https://openalex.org/W2963081547","https://openalex.org/W2963322354","https://openalex.org/W2963392702","https://openalex.org/W2980149757","https://openalex.org/W2998391154","https://openalex.org/W3001319253","https://openalex.org/W3001554227","https://openalex.org/W3009991223","https://openalex.org/W3018622322","https://openalex.org/W3048134800","https://openalex.org/W3081833727","https://openalex.org/W3100730608","https://openalex.org/W3107032263","https://openalex.org/W3110516481","https://openalex.org/W3115447952","https://openalex.org/W3133902371","https://openalex.org/W3146418728","https://openalex.org/W3169761664","https://openalex.org/W3170881570","https://openalex.org/W3170885011","https://openalex.org/W3173125503","https://openalex.org/W3174300208","https://openalex.org/W3176997885","https://openalex.org/W3188921881","https://openalex.org/W3190499751","https://openalex.org/W3195955173","https://openalex.org/W3206211787","https://openalex.org/W3207346178","https://openalex.org/W3207407006","https://openalex.org/W3207918547","https://openalex.org/W4235713725","https://openalex.org/W4244393449","https://openalex.org/W4292230951","https://openalex.org/W6628877408","https://openalex.org/W6677645113","https://openalex.org/W6739495466","https://openalex.org/W6773521587","https://openalex.org/W6785710124","https://openalex.org/W6802792668"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2465351041","https://openalex.org/W2082465502"],"abstract_inverted_index":{"As":[0],"an":[1],"emerging":[2],"paradigm":[3],"for":[4,154],"signal":[5],"acquisition":[6],"and":[7,15,18,66,74,94,102,118,129,139,145,152],"reconstruction,":[8],"compressive":[9],"sensing":[10],"(CS)":[11],"achieves":[12],"high-speed":[13],"sampling":[14,64,127],"compression":[16],"jointly":[17],"has":[19],"found":[20],"its":[21],"way":[22],"into":[23,115],"many":[24],"applications.":[25],"With":[26],"the":[27,55,62,68,78,90,99,105,124,136],"fast":[28],"growth":[29],"of":[30,38,52,70,80,109,126],"deep":[31,56,116],"learning":[32],"in":[33,43,98],"computer":[34],"vision,":[35],"various":[36,142],"methods":[37,144],"applying":[39],"neural":[40],"networks":[41],"(NNs)":[42],"CS":[44,100,110],"imaging":[45,92],"tasks":[46],"have":[47],"been":[48],"proposed.":[49],"One":[50],"category":[51],"them,":[53],"named":[54],"unrolling":[57],"network,":[58],"is":[59],"inspired":[60],"by":[61],"physical":[63],"model":[65,93],"combines":[67],"merits":[69],"both":[71],"optimization":[72,95],"model-":[73],"data-driven":[75],"methods,":[76],"becoming":[77],"mainstream":[79],"this":[81,84],"realm.":[82],"In":[83],"review":[85,89],"article,":[86],"we":[87,134],"first":[88],"inverse":[91],"algorithms":[96],"encountered":[97],"research":[101],"then":[103],"provide":[104],"recent":[106,150],"representative":[107],"developments":[108],"networks,":[111],"which":[112],"are":[113],"grouped":[114],"physics-free":[117],"physics-inspired":[119],"approaches":[120],"with":[121],"respect":[122],"to":[123],"utilization":[125],"matrix":[128],"measurement":[130],"information.":[131],"Following":[132],"this,":[133],"analyze":[135],"conceptual":[137],"connections":[138],"relationships":[140],"among":[141],"existing":[143],"present":[146],"our":[147],"perspectives":[148],"on":[149],"advances":[151],"trends":[153],"future":[155],"research.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":40},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":14}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}