{"id":"https://openalex.org/W7138061266","doi":"https://doi.org/10.1609/aaai.v40i29.39669","title":"A Novel Sliced Fused Gromov-Wasserstein Distance","display_name":"A Novel Sliced Fused Gromov-Wasserstein Distance","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138061266","doi":"https://doi.org/10.1609/aaai.v40i29.39669"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i29.39669","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39669","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39669/43630","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":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39669/43630","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068150443","display_name":"Moritz Piening","orcid":"https://orcid.org/0009-0003-3877-4511"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Moritz Piening","raw_affiliation_strings":["Technische Universit\u00e4t Berlin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Berlin","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091764895","display_name":"Robert Beinert","orcid":"https://orcid.org/0000-0002-7813-2762"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Robert Beinert","raw_affiliation_strings":["Technische Universit\u00e4t Berlin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Berlin","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37539432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"29","first_page":"24828","last_page":"24836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.23680000007152557,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.23680000007152557,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.22310000658035278,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.08129999786615372,"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/quadratic-equation","display_name":"Quadratic equation","score":0.5593000054359436},{"id":"https://openalex.org/keywords/slicing","display_name":"Slicing","score":0.5306000113487244},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.515999972820282},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5062999725341797},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.4934999942779541},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.39890000224113464},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.39559999108314514},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.3874000012874603},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3808000087738037}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6826000213623047},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C2776190703","wikidata":"https://www.wikidata.org/wiki/Q488148","display_name":"Slicing","level":2,"score":0.5306000113487244},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.515999972820282},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48420000076293945},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.39890000224113464},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.39559999108314514},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3874000012874603},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C145580432","wikidata":"https://www.wikidata.org/wiki/Q6497118","display_name":"Lattice graph","level":5,"score":0.34060001373291016},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.2773999869823456},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C62869609","wikidata":"https://www.wikidata.org/wiki/Q28137","display_name":"Quadrature (astronomy)","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.25859999656677246}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i29.39669","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39669","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39669/43630","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.v40i29.39669","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39669","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39669/43630","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138061266.pdf","grobid_xml":"https://content.openalex.org/works/W7138061266.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Gromov\u2013Wasserstein":[1],"(GW)":[2],"distance":[3,133,165],"and":[4,58,96,121,146,154,170,176,186],"its":[5,65,148],"fused":[6],"extension":[7],"(FGW)":[8],"are":[9,24],"powerful":[10],"tools":[11],"for":[12,79,84,100,138],"comparing":[13],"heterogeneous":[14],"data.":[15],"Their":[16],"computation":[17],"is,":[18],"however,":[19],"challenging":[20],"since":[21],"both":[22],"distances":[23],"based":[25,88],"on":[26,89],"non-convex,":[27],"quadratic":[28,161],"optimal":[29],"transport":[30],"(OT)":[31],"problems.":[32,105],"Leveraging":[33],"1D":[34,103],"OT,":[35,95],"a":[36,75,136],"sliced":[37,51,108,152,164],"version":[38,52],"of":[39,125,183],"GW":[40,80,175],"has":[41],"been":[42],"proposed":[43],"to":[44,55,61,118],"lower":[45,92],"the":[46,101,112,123,159,173,181],"computational":[47],"burden.":[48],"Unfortunately,":[49],"this":[50],"is":[53,87,166],"restricted":[54],"Euclidean":[56],"geometry":[57],"loses":[59],"invariance":[60],"isometries,":[62],"strongly":[63],"limiting":[64],"application":[66],"in":[67,180],"practice.":[68],"To":[69],"overcome":[70],"these":[71],"issues,":[72],"we":[73,157],"propose":[74],"novel":[76,107],"slicing":[77],"technique":[78],"as":[81,83],"well":[82],"FGW":[85,109,143,177],"that":[86,130,141],"an":[90],"appropriate":[91],"bound,":[93],"hierarchical":[94],"suitable":[97],"quadrature":[98],"rules":[99],"underlying":[102,160],"OT":[104],"Our":[106],"significantly":[110],"reduces":[111],"numerical":[113],"effort":[114],"while":[115],"remaining":[116],"invariant":[117],"isometric":[119],"transformations":[120],"allowing":[122],"comparison":[124],"arbitrary":[126],"geometries.":[127],"We":[128],"show":[129],"our":[131,163],"new":[132],"actually":[134],"defines":[135],"pseudo-metric":[137],"structured":[139],"spaces":[140],"bounds":[142],"from":[144],"below":[145],"study":[147],"interpolation":[149],"properties":[150],"between":[151],"Wasserstein":[153],"GW.":[155],"Since":[156],"avoid":[158],"program,":[162],"numerically":[167],"more":[168],"robust":[169],"reliable":[171],"than":[172],"original":[174],"distance;":[178],"especially":[179],"context":[182],"shape":[184],"retrieval":[185],"graph":[187],"isomorphism":[188],"testing.":[189]},"counts_by_year":[],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2026-03-18T00:00:00"}