{"id":"https://openalex.org/W7137919134","doi":"https://doi.org/10.1609/aaai.v40i26.39369","title":"On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples","display_name":"On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137919134","doi":"https://doi.org/10.1609/aaai.v40i26.39369"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i26.39369","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i26.39369","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i26.39369","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120655976","display_name":"Cheongjae Jang","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Cheongjae Jang","raw_affiliation_strings":["Hanyang University, Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120411516","display_name":"Jonghyun Won","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jonghyun Won","raw_affiliation_strings":["Hanyang University, Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129665451","display_name":"Soyeon Jun","orcid":null},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soyeon Jun","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai, USA\nSeoul National University, Korea"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai, USA\nSeoul National University, Korea","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129649422","display_name":"Chun Kee Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chun Kee Chung","raw_affiliation_strings":["Seoul National University, Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Keehyoung Joo","orcid":null},"institutions":[{"id":"https://openalex.org/I125608817","display_name":"Korea Institute for Advanced Study","ror":"https://ror.org/041hz9568","country_code":"KR","type":"facility","lineage":["https://openalex.org/I125608817"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Keehyoung Joo","raw_affiliation_strings":["Korea Institute for Advanced Study, Korea"],"affiliations":[{"raw_affiliation_string":"Korea Institute for Advanced Study, Korea","institution_ids":["https://openalex.org/I125608817"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120411517","display_name":"Yung-Kyun Noh","orcid":null},"institutions":[{"id":"https://openalex.org/I125608817","display_name":"Korea Institute for Advanced Study","ror":"https://ror.org/041hz9568","country_code":"KR","type":"facility","lineage":["https://openalex.org/I125608817"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yung-Kyun Noh","raw_affiliation_strings":["Hanyang University, Korea\nKorea Institute for Advanced Study, Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University, Korea\nKorea Institute for Advanced Study, Korea","institution_ids":["https://openalex.org/I125608817"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5120655976"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15384615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"26","first_page":"22137","last_page":"22145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.32839998602867126,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.32839998602867126,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.08020000159740448,"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.07850000262260437,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.8925999999046326},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.48730000853538513},{"id":"https://openalex.org/keywords/pointwise-mutual-information","display_name":"Pointwise mutual information","score":0.47369998693466187},{"id":"https://openalex.org/keywords/information-processing","display_name":"Information processing","score":0.4526999890804291},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3885999917984009},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3749000132083893},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.3580999970436096}],"concepts":[{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.8925999999046326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5746999979019165},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C7797323","wikidata":"https://www.wikidata.org/wiki/Q3798612","display_name":"Pointwise mutual information","level":3,"score":0.47369998693466187},{"id":"https://openalex.org/C87868495","wikidata":"https://www.wikidata.org/wiki/Q750843","display_name":"Information processing","level":2,"score":0.4526999890804291},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3749000132083893},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36070001125335693},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C2777634741","wikidata":"https://www.wikidata.org/wiki/Q768993","display_name":"Wasserstein metric","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30090001225471497},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.30000001192092896},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.29739999771118164},{"id":"https://openalex.org/C166144826","wikidata":"https://www.wikidata.org/wiki/Q1145117","display_name":"Poisson process","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2791999876499176},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i26.39369","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i26.39369","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i26.39369","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i26.39369","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Leveraging":[0],"the":[1,66,71,80,85,90,94,129],"Wasserstein":[2,73,99,131],"distance\u2014a":[3],"summation":[4],"of":[5,65,70,92],"sample-wise":[6],"transport":[7,43],"distances":[8,100],"in":[9,13,54],"data":[10],"space\u2014is":[11],"advantageous":[12],"many":[14],"applications":[15],"for":[16],"measuring":[17],"support":[18,107],"differences":[19,136],"between":[20],"two":[21],"underlying":[22],"density":[23,96,135],"functions.":[24],"However,":[25],"when":[26],"supports":[27],"significantly":[28],"overlap":[29],"while":[30],"densities":[31],"exhibit":[32],"substantial":[33],"pointwise":[34,95],"differences,":[35,49],"it":[36],"remains":[37],"unclear":[38],"whether":[39],"and":[40,83,101,119,141],"how":[41,102],"this":[42,59,103],"information":[44,67,104],"can":[45],"accurately":[46],"identify":[47],"these":[48],"particularly":[50],"their":[51],"analytic":[52],"characterization":[53],"finite-sample":[55],"settings.":[56],"We":[57],"address":[58],"issue":[60],"by":[61],"conducting":[62],"an":[63],"analysis":[64],"processing":[68],"capabilities":[69],"one-dimensional":[72,130],"distance":[74,132],"with":[75,98,106],"finite":[76],"samples.":[77],"By":[78],"utilizing":[79],"Poisson":[81],"process":[82],"isolating":[84],"rate":[86,140],"factor,":[87],"we":[88],"demonstrate":[89],"capability":[91],"capturing":[93],"difference":[97],"harmonizes":[105],"differences.":[108],"The":[109,125],"analyzed":[110],"properties":[111],"are":[112],"confirmed":[113],"using":[114],"neural":[115],"spike":[116],"train":[117],"decoding":[118],"amino":[120],"acid":[121],"contact":[122],"frequency":[123],"data.":[124],"results":[126],"reveal":[127],"that":[128],"highlights":[133],"meaningful":[134],"related":[137],"to":[138],"both":[139],"support.":[142]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2026-03-18T00:00:00"}
