{"id":"https://openalex.org/W4415539881","doi":"https://doi.org/10.1145/3746027.3755582","title":"Spatial Imputation Drives Cross-Domain Alignment for EEG Classification","display_name":"Spatial Imputation Drives Cross-Domain Alignment for EEG Classification","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415539881","doi":"https://doi.org/10.1145/3746027.3755582"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3755582","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.03437","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050677962","display_name":"Hongjun Liu","orcid":"https://orcid.org/0009-0002-2661-8047"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjun Liu","raw_affiliation_strings":["School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-2661-8047","affiliations":[{"raw_affiliation_string":"School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101678298","display_name":"Chao Yao","orcid":"https://orcid.org/0000-0001-5483-3225"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Yao","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5483-3225","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747319","display_name":"Yalan Zhang","orcid":"https://orcid.org/0000-0002-8736-7125"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalan Zhang","raw_affiliation_strings":["School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8736-7125","affiliations":[{"raw_affiliation_string":"School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115695206","display_name":"Xiaokun Wang","orcid":"https://orcid.org/0009-0006-8984-9212"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaokun Wang","raw_affiliation_strings":["School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-8984-9212","affiliations":[{"raw_affiliation_string":"School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009624071","display_name":"Xiaojuan Ban","orcid":"https://orcid.org/0000-0001-9142-3276"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojuan Ban","raw_affiliation_strings":["School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9142-3276","affiliations":[{"raw_affiliation_string":"School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8586","last_page":"8595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/robustness","display_name":"Robustness (evolution)","score":0.6470000147819519},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6394000053405762},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5393999814987183},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.5231999754905701},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5198000073432922},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.3522000014781952},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3497999906539917},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.32589998841285706}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232000231742859},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6470000147819519},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6394000053405762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6075999736785889},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5393999814987183},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.5231999754905701},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5198000073432922},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5015000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3555999994277954},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2939999997615814},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.2768000066280365},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2590999901294708},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2508000135421753},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746027.3755582","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2508.03437","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.03437","pdf_url":"https://arxiv.org/pdf/2508.03437","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.03437","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.03437","pdf_url":"https://arxiv.org/pdf/2508.03437","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1980208701","https://openalex.org/W2002055708","https://openalex.org/W2559463885","https://openalex.org/W2965206958","https://openalex.org/W3039181572","https://openalex.org/W3080914981","https://openalex.org/W3133542152","https://openalex.org/W3140416091","https://openalex.org/W3198543070","https://openalex.org/W3217693365","https://openalex.org/W4282958994","https://openalex.org/W4293222296","https://openalex.org/W4308243395","https://openalex.org/W4312597583","https://openalex.org/W4318833227","https://openalex.org/W4385255092","https://openalex.org/W4385453586","https://openalex.org/W4385565375","https://openalex.org/W4386869600","https://openalex.org/W4387969410","https://openalex.org/W4401024754","https://openalex.org/W4403446388","https://openalex.org/W4404576998","https://openalex.org/W4406321725","https://openalex.org/W4408131299","https://openalex.org/W4409200180"],"related_works":[],"abstract_inverted_index":{"Electroencephalogram":[0],"(EEG)":[1],"signal":[2,87,131],"classification":[3,176,210],"faces":[4],"significant":[5],"challenges":[6],"due":[7],"to":[8,124,202],"data":[9,43],"distribution":[10,195],"shifts":[11,44],"caused":[12],"by":[13,200],"heterogeneous":[14,54],"electrode":[15,55,64],"configurations,":[16],"acquisition":[17],"protocols,":[18],"and":[19,32,95,117,146,160,181,193],"hardware":[20],"discrepancies":[21],"across":[22,164],"domains.":[23],"This":[24,89],"paper":[25],"introduces":[26,85],"IMAC,":[27],"a":[28,46,67,92,100,138],"novel":[29],"channel-dependent":[30,93],"mask":[31,94],"imputation":[33,50,105],"self-supervised":[34,80],"framework":[35],"that":[36,141],"formulates":[37],"the":[38,122,126,144,150],"alignment":[39,132],"of":[40,149],"cross-domain":[41,58,111],"EEG":[42,103,151,168],"as":[45,99,114],"spatial":[47,75,104,147],"time":[48],"series":[49],"task.":[51],"To":[52],"address":[53],"configurations":[56],"in":[57,178,204],"scenarios,":[59],"IMAC":[60,84,136,186],"first":[61],"standardizes":[62],"different":[63],"layouts":[65],"using":[66],"3D-to-2D":[68],"positional":[69],"unification":[70],"mapping":[71],"strategy,":[72],"establishing":[73],"unified":[74],"representations.":[76],"Unlike":[77],"previous":[78],"mask-based":[79],"representation":[81],"learning":[82],"methods,":[83],"spatio-temporal":[86],"alignment.":[88],"involves":[90],"constructing":[91],"reconstruction":[96],"task":[97],"framed":[98],"low-to-high":[101],"resolution":[102],"problem.":[106],"Consequently,":[107],"this":[108],"approach":[109],"simulates":[110],"variations":[112],"such":[113],"channel":[115],"omissions":[116],"temporal":[118,145],"instabilities,":[119],"thus":[120],"enabling":[121],"model":[123],"leverage":[125],"proposed":[127],"imputer":[128],"for":[129],"robust":[130],"during":[133],"inference.":[134],"Furthermore,":[135],"incorporates":[137],"disentangled":[139],"structure":[140],"separately":[142],"models":[143],"information":[148],"signals":[152],"separately,":[153],"reducing":[154],"computational":[155],"complexity":[156],"while":[157,207],"enhancing":[158],"flexibility":[159],"adaptability.":[161],"Comprehensive":[162],"evaluations":[163],"10":[165],"publicly":[166],"available":[167],"datasets":[169],"demonstrate":[170],"IMAC's":[171],"superior":[172],"performance,":[173],"achieving":[174],"state-of-the-art":[175],"accuracy":[177],"both":[179,191],"cross-subject":[180],"cross-center":[182],"validation":[183],"scenarios.":[184],"Notably,":[185],"shows":[187],"strong":[188],"robustness":[189],"under":[190],"simulated":[192],"real-world":[194],"shifts,":[196],"surpassing":[197],"baseline":[198],"methods":[199],"up":[201],"35%":[203],"integrity":[205],"scores":[206],"maintaining":[208],"consistent":[209],"accuracy.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}
