{"id":"https://openalex.org/W4400558410","doi":"https://doi.org/10.1137/23m1620363","title":"A Wasserstein-Type Distance for Gaussian Mixtures on Vector Bundles with Applications to Shape Analysis","display_name":"A Wasserstein-Type Distance for Gaussian Mixtures on Vector Bundles with Applications to Shape Analysis","publication_year":2024,"publication_date":"2024-07-11","ids":{"openalex":"https://openalex.org/W4400558410","doi":"https://doi.org/10.1137/23m1620363","pmid":"https://pubmed.ncbi.nlm.nih.gov/40746640"},"language":"en","primary_location":{"id":"doi:10.1137/23m1620363","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1137/23m1620363","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12312677/pdf/nihms-2038437.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038044081","display_name":"Michael Wilson","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Wilson","raw_affiliation_strings":["Department of Statistics, Florida State University, Tallahassee, FL 32306 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Florida State University, Tallahassee, FL 32306 USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073878869","display_name":"Tom Needham","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tom Needham","raw_affiliation_strings":["Department of Mathematics, Florida State University, Tallahassee, FL 32306 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Florida State University, Tallahassee, FL 32306 USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035632114","display_name":"Chiwoo Park","orcid":"https://orcid.org/0000-0002-2463-8901"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chiwoo Park","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Washington, Seattle, WA 98195 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Washington, Seattle, WA 98195 USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114190063","display_name":"Suparteek Kundu","orcid":null},"institutions":[{"id":"https://openalex.org/I1343551460","display_name":"The University of Texas MD Anderson Cancer Center","ror":"https://ror.org/04twxam07","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1343551460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suparteek Kundu","raw_affiliation_strings":["The University of Texas MD Anderson Cancer Center, Houston, TX 77030 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas MD Anderson Cancer Center, Houston, TX 77030 USA","institution_ids":["https://openalex.org/I1343551460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086786635","display_name":"Anuj Srivastava","orcid":"https://orcid.org/0000-0001-7406-0338"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anuj Srivastava","raw_affiliation_strings":["Department of Statistics, Florida State University, Tallahassee, FL 32306 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Florida State University, Tallahassee, FL 32306 USA","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6055,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.81050246,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"17","issue":"3","first_page":"1433","last_page":"1466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.972100019454956,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.960099995136261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/vector-bundle","display_name":"Vector bundle","score":0.604107677936554},{"id":"https://openalex.org/keywords/type","display_name":"Type (biology)","score":0.5387393832206726},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5369861125946045},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4862002730369568},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3553234338760376},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35305410623550415},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.33109337091445923},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32433968782424927},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2094854712486267}],"concepts":[{"id":"https://openalex.org/C95857938","wikidata":"https://www.wikidata.org/wiki/Q658429","display_name":"Vector bundle","level":2,"score":0.604107677936554},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.5387393832206726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5369861125946045},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4862002730369568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3553234338760376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35305410623550415},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.33109337091445923},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32433968782424927},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2094854712486267},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1137/23m1620363","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1137/23m1620363","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},{"id":"pmid:40746640","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40746640","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM journal on imaging sciences","raw_type":"Journal Article"},{"id":"pmh:oai:europepmc.org:11125288","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12312677","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12312677/pdf/nihms-2038437.pdf","source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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:europepmc.org:11125288","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12312677","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12312677/pdf/nihms-2038437.pdf","source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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":[{"id":"https://openalex.org/G1836215700","display_name":"Collaborative Research: Applications of Symplectic Geometry to Frame Theory and Signal Processing","funder_award_id":"2107808","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4634608528","display_name":"Integrative Brain Network-Based Analysis for Heterogeneous and Multimodal","funder_award_id":"5r01mh120299-05","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5199417320","display_name":"CDS&E: Geometrical Regression Models Involving Complex Shape Variables","funder_award_id":"1953087","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5656183857","display_name":null,"funder_award_id":"CMMI-2132311","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"},{"id":"https://openalex.org/G5943551637","display_name":"eMB: New Approaches for Interpreting Neural Responses to Behaviorally-Relevant Sensory Stimuli","funder_award_id":"2324962","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6262787969","display_name":null,"funder_award_id":"R01 MH120299","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400558410.pdf","grobid_xml":"https://content.openalex.org/works/W4400558410.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W126423635","https://openalex.org/W1557324374","https://openalex.org/W2015913877","https://openalex.org/W2040104067","https://openalex.org/W2042424194","https://openalex.org/W2058220245","https://openalex.org/W2078179989","https://openalex.org/W2094100343","https://openalex.org/W2103096501","https://openalex.org/W2112759033","https://openalex.org/W2127674094","https://openalex.org/W2146932984","https://openalex.org/W2150427470","https://openalex.org/W2155659696","https://openalex.org/W2165168736","https://openalex.org/W2487327602","https://openalex.org/W2496344256","https://openalex.org/W2529762274","https://openalex.org/W2593205548","https://openalex.org/W2622524267","https://openalex.org/W2739381145","https://openalex.org/W2801097168","https://openalex.org/W2922491876","https://openalex.org/W2955939997","https://openalex.org/W2962886522","https://openalex.org/W2963181447","https://openalex.org/W3041629860","https://openalex.org/W3105809221","https://openalex.org/W4206333827","https://openalex.org/W4206471589","https://openalex.org/W4233762729","https://openalex.org/W4234333941","https://openalex.org/W4246202668","https://openalex.org/W4246446534","https://openalex.org/W4295632409","https://openalex.org/W4299441806","https://openalex.org/W4395481429"],"related_works":["https://openalex.org/W4287329839","https://openalex.org/W3128542573","https://openalex.org/W1560102910","https://openalex.org/W96521002","https://openalex.org/W2046178815","https://openalex.org/W2949575850","https://openalex.org/W2167313235","https://openalex.org/W3092239614","https://openalex.org/W1561757050","https://openalex.org/W2081131590"],"abstract_inverted_index":{"This":[0],"paper":[1],"uses":[2],"sample":[3],"data":[4],"to":[5,55,61,109,142],"study":[6],"the":[7,38,56,88,100,110,120,139],"problem":[8],"of":[9,31,81,84,103,113,117,127,129],"comparing":[10],"populations":[11,28,116,128],"on":[12,33,74,95],"finite-dimensional":[13],"parallelizable":[14],"Riemannian":[15],"manifolds":[16],"and":[17,36,77,115,137],"more":[18],"general":[19],"trivial":[20],"vector":[21,34],"bundles.":[22],"Utilizing":[23],"triviality,":[24],"our":[25],"framework":[26],"represents":[27],"as":[29],"mixtures":[30,73,86],"Gaussians":[32],"bundles":[35],"estimates":[37],"population":[39],"parameters":[40],"using":[41],"a":[42,48,78,125,134],"mode-based":[43],"clustering":[44],"algorithm.":[45],"We":[46,91],"derive":[47],"Wasserstein-type":[49,140],"metric":[50],"between":[51],"Gaussian":[52,72,85],"mixtures,":[53],"adapted":[54],"manifold":[57,75],"geometry,":[58],"in":[59],"order":[60],"compare":[62],"estimated":[63],"distributions.":[64],"Our":[65],"contributions":[66],"include":[67],"an":[68],"identifiability":[69],"result":[70],"for":[71],"domains":[76],"convenient":[79],"characterization":[80],"optimal":[82],"couplings":[83],"under":[87],"derived":[89],"metric.":[90],"demonstrate":[92],"these":[93],"tools":[94],"some":[96],"example":[97],"domains,":[98],"including":[99],"preshape":[101],"space":[102,112],"planar":[104],"closed":[105],"curves,":[106],"with":[107],"applications":[108],"shape":[111],"triangles":[114],"nanoparticles.":[118],"In":[119],"nanoparticle":[121],"application,":[122],"we":[123],"consider":[124],"sequence":[126],"particle":[130],"shapes":[131],"arising":[132],"from":[133],"manufacturing":[135],"process":[136],"utilize":[138],"distance":[141],"perform":[143],"change-point":[144],"detection.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}
