{"id":"https://openalex.org/W7140220029","doi":"https://doi.org/10.48550/arxiv.2603.21042","title":"Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decoding","display_name":"Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decoding","publication_year":2026,"publication_date":"2026-03-22","ids":{"openalex":"https://openalex.org/W7140220029","doi":"https://doi.org/10.48550/arxiv.2603.21042"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21042","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21042","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xu, Shuoxun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Shuoxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yan, Zhanhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Zhanhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Li, Lexin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lexin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.6608999967575073,"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/T11094","display_name":"Face Recognition and Perception","score":0.6608999967575073,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0966000035405159,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.06689999997615814,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7563999891281128},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5964999794960022},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5436999797821045},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5371000170707703},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4952000081539154},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.49399998784065247},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.484499990940094},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.4681999981403351}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7563999891281128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7257999777793884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6216999888420105},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5964999794960022},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5436999797821045},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5371000170707703},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4952000081539154},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.4681999981403351},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40799999237060547},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3953999876976013},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21042","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21042","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Brain":[0],"encoding":[1,32],"and":[2,12,15,33,47,75,78,93,107,116,125,128],"decoding":[3],"aims":[4],"to":[5],"understand":[6],"the":[7,101,134],"relationship":[8],"between":[9],"external":[10],"stimuli":[11],"brain":[13,31],"activities,":[14],"is":[16],"a":[17,36,53],"fundamental":[18],"problem":[19],"in":[20],"neuroscience.":[21],"In":[22],"this":[23],"article,":[24],"we":[25],"study":[26],"latent":[27],"embedding":[28],"alignment":[29,55,102],"for":[30,111],"decoding,":[34],"with":[35,58],"focus":[37],"on":[38,133],"improving":[39],"sample":[40],"efficiency":[41],"under":[42],"limited":[43],"fMRI-stimulus":[44],"paired":[45],"data":[46],"substantial":[48],"subject":[49],"heterogeneity.":[50],"We":[51,120],"propose":[52],"lightweight":[54],"framework":[56],"equipped":[57],"two":[59],"statistical":[60],"learning":[61,65,81],"components:":[62],"inverse":[63,73],"semi-supervised":[64],"that":[66,82],"leverages":[67],"abundant":[68],"unpaired":[69],"stimulus":[70],"embeddings":[71],"through":[72],"mapping":[74],"residual":[76,94],"debiasing,":[77],"meta":[79],"transfer":[80],"borrows":[83],"strength":[84],"from":[85],"pretrained":[86],"models":[87],"across":[88],"subjects":[89],"via":[90],"sparse":[91],"aggregation":[92],"correction.":[95],"Both":[96],"methods":[97],"operate":[98],"exclusively":[99],"at":[100],"stage":[103],"while":[104],"keeping":[105],"encoders":[106],"decoders":[108],"frozen,":[109],"allowing":[110],"efficient":[112],"computation,":[113],"modular":[114],"deployment,":[115],"rigorous":[117],"theoretical":[118],"analysis.":[119],"establish":[121],"finite-sample":[122],"generalization":[123],"bounds":[124],"safety":[126],"guarantees,":[127],"demonstrate":[129],"competitive":[130],"empirical":[131],"performance":[132],"large-scale":[135],"fMRI-image":[136],"reconstruction":[137],"benchmark":[138],"data.":[139]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-25T00:00:00"}