{"id":"https://openalex.org/W4400519205","doi":"https://doi.org/10.48550/arxiv.2407.07059","title":"Differentiable Optimization of Similarity Scores Between Models and Brains","display_name":"Differentiable Optimization of Similarity Scores Between Models and Brains","publication_year":2024,"publication_date":"2024-07-09","ids":{"openalex":"https://openalex.org/W4400519205","doi":"https://doi.org/10.48550/arxiv.2407.07059"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.07059","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.07059","pdf_url":"https://arxiv.org/pdf/2407.07059","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.07059","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071331799","display_name":"Nathan Cloos","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cloos, Nathan","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078339634","display_name":"Moufan Li","orcid":"https://orcid.org/0009-0004-6611-9124","observed_orcids":["https://orcid.org/0009-0004-6611-9124"]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li, Moufan","raw_affiliation_strings":["NYU"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NYU","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063636409","display_name":"Markus Siegel","orcid":"https://orcid.org/0000-0001-5115-936X","observed_orcids":["https://orcid.org/0000-0001-5115-936X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siegel, Markus","raw_affiliation_strings":["HIH T\u00fcbingen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HIH T\u00fcbingen","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080355615","display_name":"Scott L. Brincat","orcid":"https://orcid.org/0000-0002-7777-7294","observed_orcids":["https://orcid.org/0000-0002-7777-7294"]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brincat, Scott L.","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084251670","display_name":"Earl K. Miller","orcid":"https://orcid.org/0000-0002-0582-6958","observed_orcids":["https://orcid.org/0000-0002-0582-6958"]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Miller, Earl K.","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053839400","display_name":"Guangyu Robert Yang","orcid":"https://orcid.org/0000-0002-8919-4248","observed_orcids":["https://orcid.org/0000-0002-8919-4248"]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang, Guangyu Robert","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059572012","display_name":"Christopher J. Cueva","orcid":"https://orcid.org/0000-0002-0761-6161","observed_orcids":["https://orcid.org/0000-0002-0761-6161"]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cueva, Christopher J.","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":9,"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/T10320","display_name":"Neural Networks and Applications","score":0.5044000148773193,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.5044000148773193,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2506999969482422,"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"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.06780000030994415,"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/similarity-measures","display_name":"similarity measures","score":0.5950000286102295},{"id":"https://openalex.org/keywords/differentiable-optimization","display_name":"differentiable optimization","score":0.7649999856948853},{"id":"https://openalex.org/keywords/centered-kernel-alignment","display_name":"centered kernel alignment","score":0.9010000228881836},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.7379999756813049},{"id":"https://openalex.org/keywords/neural-coding","display_name":"neural coding","score":0.6269999742507935},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"synthetic data","score":0.460999995470047}],"concepts":[{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.7004870176315308},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6966816782951355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4416697323322296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39151251316070557},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.3489990830421448},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3095921576023102},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.218727707862854},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.1805902123451233},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.07059","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.07059","pdf_url":"https://arxiv.org/pdf/2407.07059","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.07059","doi":"https://doi.org/10.48550/arxiv.2407.07059","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.07059","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.07059","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.07059","pdf_url":"https://arxiv.org/pdf/2407.07059","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400519205.pdf","grobid_xml":"https://content.openalex.org/works/W4400519205.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W1480668978","https://openalex.org/W2058616551","https://openalex.org/W2121008432"],"related_works":["https://openalex.org/W4404407007","https://openalex.org/W4401451734","https://openalex.org/W7083691842","https://openalex.org/W7214079902","https://openalex.org/W7080289203","https://openalex.org/W7058093475","https://openalex.org/W7101430490","https://openalex.org/W7160636447","https://openalex.org/W4409242850","https://openalex.org/W4416507625"],"abstract_inverted_index":{"How":[0],"do":[1,87],"we":[2,61,81,178,213,256],"know":[3],"if":[4],"two":[5],"systems":[6],"-":[7,11,127],"biological":[8],"or":[9],"artificial":[10],"process":[12],"information":[13,92],"in":[14,93],"a":[15,57,63,94,123,233],"similar":[16],"way?":[17],"Similarity":[18,30],"measures":[19,74,223,231],"such":[20],"as":[21],"linear":[22,115],"regression,":[23],"Centered":[24],"Kernel":[25],"Alignment":[26],"(CKA),":[27],"Normalized":[28],"Bures":[29],"(NBS),":[31],"and":[32,53,100,107,113,134,187,196,218,267],"angular":[33,161,185],"Procrustes":[34,162],"distance,":[35],"are":[36,224],"often":[37],"used":[38,260],"to":[39,66,75,142,189,237,263],"quantify":[40,238],"this":[41,101],"similarity.":[42],"However,":[43],"it":[44,128],"is":[45,102],"currently":[46],"unclear":[47],"what":[48,55],"drives":[49],"high":[50,84,203],"similarity":[51,73,85,125,144,211,222,240,269],"scores":[52,86,145],"even":[54,108],"constitutes":[56],"\"good\"":[58],"score.":[59,79],"Here,":[60],"introduce":[62],"novel":[64],"tool":[65],"investigate":[67],"these":[68],"questions":[69],"by":[70,207,261],"differentiating":[71],"through":[72],"directly":[76],"maximize":[77,143],"the":[78,132,135,148,154,181,190,198,239,247,254],"Surprisingly,":[80],"find":[82,118],"that":[83,220],"not":[88],"guarantee":[89],"encoding":[90],"task-relevant":[91],"manner":[95],"consistent":[96,120],"with":[97],"neural":[98,242],"data;":[99],"particularly":[103],"acute":[104],"for":[105,122,249],"CKA":[106,200],"some":[109,158,221],"variations":[110],"of":[111,153,183,192],"cross-validated":[112],"regularized":[114],"regression.":[116],"We":[117,252],"no":[119],"threshold":[121],"good":[124],"score":[126],"depends":[129],"on":[130,176,202],"both":[131],"measure":[133],"dataset.":[136],"In":[137],"addition,":[138],"synthetic":[139],"datasets":[140],"optimized":[141],"initially":[146],"learn":[147],"highest":[149],"variance":[150,165,191,204],"principal":[151,193],"component":[152,194],"target":[155],"dataset,":[156],"but":[157],"methods":[159,170],"like":[160,171],"capture":[163],"lower":[164],"dimensions":[166],"much":[167],"earlier":[168],"than":[169,227],"CKA.":[172],"To":[173],"shed":[174],"light":[175],"this,":[177],"mathematically":[179],"derive":[180],"sensitivity":[182],"CKA,":[184],"Procrustes,":[186],"NBS":[188],"dimensions,":[195],"explain":[197],"emphasis":[199],"places":[201],"components.":[205],"Finally,":[206],"jointly":[208],"optimizing":[209],"multiple":[210],"measures,":[212],"characterize":[214],"their":[215],"allowable":[216],"ranges":[217],"reveal":[219],"more":[225],"constraining":[226],"others.":[228],"While":[229],"current":[230,266],"offer":[232],"seemingly":[234],"straightforward":[235],"way":[236],"between":[241],"systems,":[243],"our":[244],"work":[245],"underscores":[246],"need":[248],"careful":[250],"interpretation.":[251],"hope":[253],"tools":[255],"developed":[257],"will":[258],"be":[259],"practitioners":[262],"better":[264],"understand":[265],"future":[268],"measures.":[270]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-07-11T00:00:00"}