{"id":"https://openalex.org/W4408355562","doi":"https://doi.org/10.1109/icassp49660.2025.10890733","title":"Wasserstein Heterogeneous Graph Neural Networks for Uncertainty-Aware Anomaly Detection","display_name":"Wasserstein Heterogeneous Graph Neural Networks for Uncertainty-Aware Anomaly Detection","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355562","doi":"https://doi.org/10.1109/icassp49660.2025.10890733"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890733","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890733","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 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/A5100418485","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0002-7099-7905"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Chen","raw_affiliation_strings":["Beihang University,School of Cyber Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Cyber Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102722435","display_name":"Yunchun Li","orcid":"https://orcid.org/0000-0003-0809-2619"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunchun Li","raw_affiliation_strings":["Beihang University,School of Computer Science and Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Computer Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Boxuan Jiao","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boxuan Jiao","raw_affiliation_strings":["Beihang University,School of Cyber Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Cyber Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100896288","display_name":"Guorui Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guorui Zhao","raw_affiliation_strings":["Beihang University,School of Computer Science and Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Computer Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100318397","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-2152-4172"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Beihang University,Key Laboratory of Networking,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,Key Laboratory of Networking,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/anomaly-detection","display_name":"Anomaly detection","score":0.8004755973815918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7133216261863708},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49408748745918274},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4410092234611511},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4340142607688904},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42668479681015015},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.335446298122406},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2461056113243103}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8004755973815918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7133216261863708},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49408748745918274},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4410092234611511},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4340142607688904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42668479681015015},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.335446298122406},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2461056113243103},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","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/icassp49660.2025.10890733","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890733","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1594039573","https://openalex.org/W2075010670","https://openalex.org/W2089554624","https://openalex.org/W2127979711","https://openalex.org/W2790344751","https://openalex.org/W2807841289","https://openalex.org/W2911286998","https://openalex.org/W2944250323","https://openalex.org/W2963893312","https://openalex.org/W2964051675","https://openalex.org/W2965857891","https://openalex.org/W2970127247","https://openalex.org/W2992818769","https://openalex.org/W2998336824","https://openalex.org/W3004507689","https://openalex.org/W3012871709","https://openalex.org/W3031781733","https://openalex.org/W3048072497","https://openalex.org/W3115798218","https://openalex.org/W3209441117","https://openalex.org/W4221095033","https://openalex.org/W4327522204","https://openalex.org/W4379927591","https://openalex.org/W4386973209","https://openalex.org/W4391120603","https://openalex.org/W4400770860","https://openalex.org/W6726873649","https://openalex.org/W6729835178","https://openalex.org/W6730084236","https://openalex.org/W6738964360","https://openalex.org/W6743555512","https://openalex.org/W6760045743","https://openalex.org/W6765721576","https://openalex.org/W6766978945","https://openalex.org/W6795548309","https://openalex.org/W6810969505"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Graph":[0,32],"anomaly":[1],"detection,":[2,24],"a":[3,96],"critical":[4],"topic":[5],"in":[6,42,107],"graph":[7,84,99],"mining,":[8],"has":[9],"garnered":[10],"significant":[11,144],"research":[12],"interest":[13],"and":[14,28,56,83,118,132,154],"found":[15],"applications":[16],"across":[17],"diverse":[18],"domains":[19],"such":[20],"as":[21,38],"attack":[22],"event":[23],"spam":[25],"review":[26],"identification,":[27],"financial":[29],"fraud":[30],"prevention.":[31],"Neural":[33],"Networks":[34],"(GNNs)":[35],"have":[36],"emerged":[37],"the":[39,164],"dominant":[40],"approach":[41,111],"this":[43],"field.":[44],"Conventional":[45],"GNN-based":[46],"methods":[47,74],"typically":[48],"aggregate":[49],"neighbor":[50],"information":[51],"to":[52,77,87,115,122],"learn":[53],"node":[54,105],"embeddings":[55],"reconstruct":[57],"structural":[58],"relationships":[59],"or":[60],"attributes,":[61],"assuming":[62],"normal":[63],"nodes":[64],"exhibit":[65],"lower":[66],"reconstruction":[67,127],"errors":[68],"than":[69],"anomalous":[70],"ones.":[71],"However,":[72],"these":[73,92],"often":[75],"fail":[76],"account":[78],"for":[79],"uncertainty,":[80],"higher-order":[81],"structures,":[82],"heterogeneity,":[85],"leading":[86],"suboptimal":[88],"performance.":[89],"To":[90],"address":[91],"limitations,":[93],"we":[94],"propose":[95],"novel":[97],"heterogeneous":[98],"neural":[100],"network":[101],"that":[102,138],"learns":[103],"distribution-based":[104],"representations":[106],"Wasserstein":[108,120],"space.":[109],"Our":[110],"leverages":[112],"Gaussian":[113],"distributions":[114],"capture":[116],"uncertainty":[117],"employs":[119],"distance":[121],"preserve":[123],"transitivity,":[124],"while":[125],"incorporating":[126],"losses":[128],"at":[129],"structural,":[130],"attribute,":[131],"type":[133],"levels.":[134],"Experimental":[135],"results":[136],"demonstrate":[137],"our":[139,167],"proposed":[140],"W-HGAD":[141],"model":[142],"achieves":[143],"improvements":[145],"over":[146],"state-of-the-art":[147],"methods,":[148],"with":[149],"AUC":[150],"increases":[151],"of":[152,166],"9.46%":[153],"5.69%":[155],"on":[156],"two":[157],"benchmark":[158],"datasets.":[159],"Ablation":[160],"studies":[161],"further":[162],"validate":[163],"effectiveness":[165],"model\u2019s":[168],"key":[169],"components.":[170]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}