{"id":"https://openalex.org/W4392904069","doi":"https://doi.org/10.1109/icassp48485.2024.10447922","title":"A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings","display_name":"A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392904069","doi":"https://doi.org/10.1109/icassp48485.2024.10447922"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447922","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10447922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019071473","display_name":"Michael Scholkemper","orcid":"https://orcid.org/0000-0002-3669-8119"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Scholkemper","raw_affiliation_strings":["RWTH Aachen University,Department of Computer Science,Germany","Department of Computer Science, RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Department of Computer Science,Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Department of Computer Science, RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114117753","display_name":"Damin K\u00fchn","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Damin K\u00fchn","raw_affiliation_strings":["RWTH Aachen University,Department of Computer Science,Germany","Department of Computer Science, RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Department of Computer Science,Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Department of Computer Science, RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093679016","display_name":"Gerion Nabbefeld","orcid":"https://orcid.org/0009-0008-5416-6352"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gerion Nabbefeld","raw_affiliation_strings":["RWTH Aachen University,Department of Biology,Germany","Department of Biology, RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Department of Biology,Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Department of Biology, RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081999331","display_name":"Simon Musall","orcid":"https://orcid.org/0000-0002-9461-1042"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Simon Musall","raw_affiliation_strings":["RWTH Aachen University,Department of Biology,Germany","Department of Biology, RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Department of Biology,Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Department of Biology, RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071984713","display_name":"Bj\u00f6rn M. Kampa","orcid":"https://orcid.org/0000-0002-4343-2634"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bj\u00f6rn Kampa","raw_affiliation_strings":["RWTH Aachen University,Department of Biology,Germany","Department of Biology, RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Department of Biology,Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Department of Biology, RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008584000","display_name":"Michael T. Schaub","orcid":"https://orcid.org/0000-0003-2426-6404"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael T. Schaub","raw_affiliation_strings":["RWTH Aachen University,Department of Computer Science,Germany","Department of Computer Science, RWTH Aachen University, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Department of Computer Science,Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"Department of Computer Science, RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I887968799"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9991999864578247,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9991999864578247,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9908999800682068,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6511399745941162},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6160790324211121},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5856680274009705},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5255478620529175},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4865190386772156},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4794979691505432},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.45484694838523865},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4097166061401367},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37655460834503174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3161073923110962},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19006910920143127}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6511399745941162},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6160790324211121},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5856680274009705},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5255478620529175},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4865190386772156},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4794979691505432},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.45484694838523865},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4097166061401367},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37655460834503174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3161073923110962},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19006910920143127},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447922","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10447922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2302795432","display_name":null,"funder_award_id":"RTG 2236","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"},{"id":"https://openalex.org/F4320328599","display_name":"Ministerium f\u00fcr Kultur und Wissenschaft des Landes Nordrhein-Westfalen","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1555966838","https://openalex.org/W1974565082","https://openalex.org/W1978710835","https://openalex.org/W1982686804","https://openalex.org/W1983681808","https://openalex.org/W2008620264","https://openalex.org/W2009494091","https://openalex.org/W2027842533","https://openalex.org/W2061564920","https://openalex.org/W2096173332","https://openalex.org/W2108288396","https://openalex.org/W2112090702","https://openalex.org/W2122111042","https://openalex.org/W2164727176","https://openalex.org/W2167822639","https://openalex.org/W2169015768","https://openalex.org/W2219166000","https://openalex.org/W2280009513","https://openalex.org/W2417433140","https://openalex.org/W2737925311","https://openalex.org/W2786672974","https://openalex.org/W2888468122","https://openalex.org/W2898267661","https://openalex.org/W2911397097","https://openalex.org/W2948839854","https://openalex.org/W2951975928","https://openalex.org/W2952729407","https://openalex.org/W2959656158","https://openalex.org/W2962756421","https://openalex.org/W2987509417","https://openalex.org/W3003315801","https://openalex.org/W3035060828","https://openalex.org/W3036377857","https://openalex.org/W3143219376","https://openalex.org/W3156257261","https://openalex.org/W3179161883","https://openalex.org/W3197089777","https://openalex.org/W3206137855","https://openalex.org/W4200480299","https://openalex.org/W4211041253","https://openalex.org/W4283796272","https://openalex.org/W4293557896","https://openalex.org/W6639578392","https://openalex.org/W6676085441","https://openalex.org/W6741450815","https://openalex.org/W6748816842","https://openalex.org/W6794192968","https://openalex.org/W6808408049"],"related_works":["https://openalex.org/W4255837520","https://openalex.org/W2387011115","https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W4234808182","https://openalex.org/W2382043075","https://openalex.org/W3130349901","https://openalex.org/W2809151339","https://openalex.org/W1578916557"],"abstract_inverted_index":{"Distance":[0],"measures":[1],"between":[2,28,56],"graphs":[3,37],"are":[4],"important":[5],"primitives":[6],"for":[7,75,88],"a":[8,26],"variety":[9],"of":[10,36,45,100,109,119],"learning":[11],"tasks.":[12],"In":[13],"this":[14,89,110],"work,":[15],"we":[16],"describe":[17],"an":[18,63],"unsupervised,":[19],"optimal":[20],"transport":[21],"based":[22],"approach":[23],"to":[24,33,43,136],"define":[25],"distance":[27,55,68,112],"graphs.":[29],"Our":[30],"idea":[31],"is":[32],"derive":[34],"representations":[35],"as":[38],"Gaussian":[39,58,103],"mixture":[40,59,104],"models,":[41],"fitted":[42],"distributions":[44,60],"sampled":[46],"node":[47],"embeddings":[48,87],"over":[49],"the":[50,76,98,101],"same":[51],"space.":[52],"The":[53],"Wasserstein":[54,111],"these":[57],"then":[61],"yields":[62],"interpretable":[64],"and":[65,91,126],"easily":[66],"computable":[67],"measure,":[69],"which":[70],"can":[71,113],"further":[72,106],"be":[73,114],"tailored":[74],"comparison":[77],"at":[78],"hand":[79],"by":[80],"choosing":[81],"appropriate":[82],"embeddings.":[83],"We":[84],"propose":[85],"two":[86],"framework":[90],"show":[92],"that":[93],"under":[94],"certain":[95],"assumptions":[96],"about":[97],"shape":[99],"resulting":[102],"components,":[105],"computational":[107],"improvements":[108],"achieved.":[115],"An":[116],"empirical":[117],"validation":[118],"our":[120],"find-":[121],"ings":[122],"on":[123],"synthetic":[124],"data":[125],"real-world":[127],"Functional":[128],"Brain":[129],"Connectivity":[130],"networks":[131],"shows":[132],"promising":[133],"performance":[134],"compared":[135],"existing":[137],"em-":[138],"bedding":[139],"methods.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}