{"id":"https://openalex.org/W4226391017","doi":"https://doi.org/10.1109/tit.2022.3163342","title":"Macroscopic Analysis of Vector Approximate Message Passing in a Model-Mismatched Setting","display_name":"Macroscopic Analysis of Vector Approximate Message Passing in a Model-Mismatched Setting","publication_year":2022,"publication_date":"2022-03-30","ids":{"openalex":"https://openalex.org/W4226391017","doi":"https://doi.org/10.1109/tit.2022.3163342"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2022.3163342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2022.3163342","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","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/A5101691372","display_name":"T. Takahashi","orcid":"https://orcid.org/0000-0002-0173-5370"},"institutions":[{"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":true,"raw_author_name":"Takashi Takahashi","raw_affiliation_strings":["Department of Physics, Graduate School of Science, Institute for Physics of Intelligence, The University of Tokyo, Bunkyo City, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-0173-5370","affiliations":[{"raw_affiliation_string":"Department of Physics, Graduate School of Science, Institute for Physics of Intelligence, The University of Tokyo, Bunkyo City, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002600110","display_name":"Yoshiyuki Kabashima","orcid":"https://orcid.org/0000-0002-2949-7108"},"institutions":[{"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":"Yoshiyuki Kabashima","raw_affiliation_strings":["Department of Physics, Graduate School of Science, Institute for Physics of Intelligence, The University of Tokyo, Bunkyo City, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-2949-7108","affiliations":[{"raw_affiliation_string":"Department of Physics, Graduate School of Science, Institute for Physics of Intelligence, The University of Tokyo, Bunkyo City, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101691372"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":1.1903,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7703469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"68","issue":"8","first_page":"5579","last_page":"5600"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.994700014591217,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.994700014591217,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/replica","display_name":"Replica","score":0.7891364097595215},{"id":"https://openalex.org/keywords/statistical-mechanics","display_name":"Statistical mechanics","score":0.663215160369873},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5575881600379944},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.5256353616714478},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4820731282234192},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4718618094921112},{"id":"https://openalex.org/keywords/symmetry-breaking","display_name":"Symmetry breaking","score":0.44902029633522034},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.43551674485206604},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4135909676551819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3962128162384033},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.31735581159591675},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.25704336166381836},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10074979066848755},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09501591324806213}],"concepts":[{"id":"https://openalex.org/C2775937380","wikidata":"https://www.wikidata.org/wiki/Q1232589","display_name":"Replica","level":2,"score":0.7891364097595215},{"id":"https://openalex.org/C99874945","wikidata":"https://www.wikidata.org/wiki/Q188715","display_name":"Statistical mechanics","level":2,"score":0.663215160369873},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5575881600379944},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.5256353616714478},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4820731282234192},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4718618094921112},{"id":"https://openalex.org/C204795200","wikidata":"https://www.wikidata.org/wiki/Q903282","display_name":"Symmetry breaking","level":2,"score":0.44902029633522034},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.43551674485206604},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4135909676551819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3962128162384033},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.31735581159591675},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.25704336166381836},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10074979066848755},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09501591324806213},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2022.3163342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2022.3163342","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1452307493","display_name":null,"funder_award_id":"JPMJCR1912","funder_id":"https://openalex.org/F4320338075","funder_display_name":"Core Research for Evolutional Science and Technology"},{"id":"https://openalex.org/G2463757768","display_name":null,"funder_award_id":"19J0711","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3497566285","display_name":null,"funder_award_id":"17H00764","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7142492827","display_name":null,"funder_award_id":"21K21310","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W121410702","https://openalex.org/W1934021597","https://openalex.org/W1959879694","https://openalex.org/W1973494188","https://openalex.org/W1977099572","https://openalex.org/W1984830458","https://openalex.org/W1991904924","https://openalex.org/W2000828982","https://openalex.org/W2019058505","https://openalex.org/W2030450972","https://openalex.org/W2032781595","https://openalex.org/W2033606703","https://openalex.org/W2048269188","https://openalex.org/W2073521724","https://openalex.org/W2087016193","https://openalex.org/W2087603457","https://openalex.org/W2088406700","https://openalex.org/W2096680158","https://openalex.org/W2101936356","https://openalex.org/W2151781750","https://openalex.org/W2160051394","https://openalex.org/W2161278885","https://openalex.org/W2228653206","https://openalex.org/W2540066350","https://openalex.org/W2566505556","https://openalex.org/W2610971674","https://openalex.org/W2723734710","https://openalex.org/W2788412124","https://openalex.org/W2918745211","https://openalex.org/W2921637050","https://openalex.org/W2945463326","https://openalex.org/W2962760202","https://openalex.org/W2963064298","https://openalex.org/W2963072996","https://openalex.org/W2963405909","https://openalex.org/W2963602028","https://openalex.org/W2963886912","https://openalex.org/W2963948465","https://openalex.org/W2975426285","https://openalex.org/W3009717121","https://openalex.org/W3015536096","https://openalex.org/W3021124331","https://openalex.org/W3034356386","https://openalex.org/W3034368263","https://openalex.org/W3046453410","https://openalex.org/W3080443566","https://openalex.org/W3095006753","https://openalex.org/W3098848552","https://openalex.org/W3101693249","https://openalex.org/W3102677399","https://openalex.org/W3103257261","https://openalex.org/W3104705077","https://openalex.org/W3106214974","https://openalex.org/W3121355058","https://openalex.org/W3200704634","https://openalex.org/W4206502013","https://openalex.org/W4211095429","https://openalex.org/W4248709896","https://openalex.org/W4292482091","https://openalex.org/W6640231202","https://openalex.org/W6681107968","https://openalex.org/W6779672848","https://openalex.org/W6781530193"],"related_works":["https://openalex.org/W2064615256","https://openalex.org/W2084723463","https://openalex.org/W3105001040","https://openalex.org/W1978652044","https://openalex.org/W3105742704","https://openalex.org/W3138689768","https://openalex.org/W1629789693","https://openalex.org/W2028305394","https://openalex.org/W4286850519","https://openalex.org/W4226391017"],"abstract_inverted_index":{"In":[0],"this":[1,75,125],"study,":[2],"macroscopic":[3],"properties":[4],"of":[5,15,26,59,66,74,132,142,174,184,235],"the":[6,30,37,52,55,63,69,80,91,100,111,116,130,139,151,165,171,181,213,222,229,236],"vector":[7],"approximate":[8],"message":[9,194],"passing":[10],"(VAMP)":[11],"algorithm":[12],"for":[13,150,214,220],"inference":[14,114],"generalized":[16],"linear":[17],"models":[18],"are":[19],"investigated":[20],"using":[21],"a":[22,41,95,188],"non-rigorous":[23,56,230],"heuristic":[24],"method":[25,173],"statistical":[27,60,175],"mechanics":[28,61],"when":[29,79,90],"true":[31],"posterior":[32],"cannot":[33],"be":[34],"used":[35],"and":[36,62,85,155],"measurement":[38,81,92],"matrix":[39,46,82,93,98],"is":[40,50,77,127,161,226],"sample":[42],"from":[43],"rotation-invariant":[44,97],"random":[45],"ensembles.":[47],"The":[48,72,121,210,233],"focus":[49],"on":[51],"correspondence":[53,73,101],"between":[54],"replica":[57,166,172,223,231],"analysis":[58],"performance":[64],"assessment":[65],"VAMP":[67,148,185,200],"in":[68,124],"model-mismatched":[70,153],"setting.":[71],"kind":[76],"well-known":[78],"has":[83,102],"independent":[84],"identically":[86],"distributed":[87],"entries.":[88],"However,":[89],"follows":[94],"general":[96],"ensemble,":[99],"been":[103],"validated":[104],"only":[105],"under":[106],"limited":[107],"cases,":[108],"such":[109,133],"as":[110],"Bayes":[112],"optimal":[113],"or":[115],"convex":[117],"empirical":[118],"risk":[119],"minimization.":[120],"result":[122],"presented":[123],"paper":[126],"to":[128,197,207],"extend":[129],"scope":[131],"correspondence.":[134],"Herein,":[135],"we":[136],"heuristically":[137],"derive":[138],"explicit":[140],"formula":[141],"state-evolution":[143],"equations,":[144],"which":[145,191],"macroscopically":[146,203],"describe":[147],"dynamics":[149],"current":[152],"case,":[154],"show":[156,179],"that":[157,180,193,219,225],"their":[158,202],"fixed":[159,182,208],"point":[160,183],"generally":[162],"consistent":[163],"with":[164,218],"symmetric":[167],"solution":[168],"obtained":[169],"by":[170,199],"mechanics.":[176],"We":[177],"also":[178],"can":[186],"exhibit":[187],"microscopic":[189,215],"instability,":[190],"indicates":[192],"variables":[195],"continue":[196],"move":[198],"while":[201],"summarized":[204],"quantities":[205],"converge":[206],"values.":[209],"critical":[211],"condition":[212],"instability":[216],"agrees":[217],"breaking":[221],"symmetry":[224],"derived":[227],"within":[228],"analysis.":[232],"results":[234],"numerical":[237],"experiments":[238],"cross-check":[239],"our":[240],"findings.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-05-05T00:00:00"}
