{"id":"https://openalex.org/W4413318926","doi":"https://doi.org/10.1109/tbdata.2025.3600004","title":"VDDFormer: A Variable Dependency Discrepancy-Based Transformer for Multivariate Time Series Anomaly Detection","display_name":"VDDFormer: A Variable Dependency Discrepancy-Based Transformer for Multivariate Time Series Anomaly Detection","publication_year":2025,"publication_date":"2025-08-19","ids":{"openalex":"https://openalex.org/W4413318926","doi":"https://doi.org/10.1109/tbdata.2025.3600004"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2025.3600004","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2025.3600004","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"type":"article","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/A5113216000","display_name":"Bo Liu","orcid":"https://orcid.org/0009-0003-0910-5722"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China","Harbin Institute of Technology, China"],"raw_orcid":"https://orcid.org/0009-0003-0910-5722","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lingling Tao","orcid":"https://orcid.org/0000-0002-2928-0902"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingling Tao","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2928-0902","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055100970","display_name":"Xiaodan Chen","orcid":"https://orcid.org/0009-0005-2377-947X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodan Chen","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China","Harbin Institute of Technology, China"],"raw_orcid":"https://orcid.org/0009-0005-2377-947X","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100450015","display_name":"Zhijun Li","orcid":"https://orcid.org/0000-0001-9129-9957"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijun Li","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China","Harbin Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-9129-9957","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0974404,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"1","first_page":"34","last_page":"46"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"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":0.9993000030517578,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9433000087738037,"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":0.7186657190322876},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6814931035041809},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6525217294692993},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6110866665840149},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5378152132034302},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5222019553184509},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4425743818283081},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4363424479961395},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41474050283432007},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3449385166168213},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34363874793052673},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33375614881515503},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1968306005001068},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1895030438899994},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09203594923019409},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07963410019874573}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7186657190322876},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6814931035041809},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6525217294692993},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6110866665840149},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5378152132034302},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5222019553184509},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4425743818283081},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4363424479961395},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41474050283432007},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3449385166168213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34363874793052673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33375614881515503},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1968306005001068},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1895030438899994},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09203594923019409},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07963410019874573},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2025.3600004","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2025.3600004","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1970088130","https://openalex.org/W2055081158","https://openalex.org/W2103914106","https://openalex.org/W2132870739","https://openalex.org/W2296719434","https://openalex.org/W2407991977","https://openalex.org/W2593048559","https://openalex.org/W2621033546","https://openalex.org/W2625602624","https://openalex.org/W2743241343","https://openalex.org/W2785362611","https://openalex.org/W2786827964","https://openalex.org/W2911200746","https://openalex.org/W2950361482","https://openalex.org/W2962736999","https://openalex.org/W2963166639","https://openalex.org/W2965433388","https://openalex.org/W3080253043","https://openalex.org/W3081497074","https://openalex.org/W3093787659","https://openalex.org/W3093823951","https://openalex.org/W3128634608","https://openalex.org/W3133518153","https://openalex.org/W3152507776","https://openalex.org/W3169450514","https://openalex.org/W3170937175","https://openalex.org/W3170981104","https://openalex.org/W3177318507","https://openalex.org/W3188872815","https://openalex.org/W3193812480","https://openalex.org/W4220730340","https://openalex.org/W4254182148","https://openalex.org/W4285600291","https://openalex.org/W4366147756","https://openalex.org/W4372342073","https://openalex.org/W4382239890","https://openalex.org/W4385245566","https://openalex.org/W4387846370","https://openalex.org/W4392309171"],"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":{"The":[0,76,108],"dynamics":[1],"of":[2,183],"multivariate":[3],"time":[4,22],"series":[5,23],"(MTS)":[6],"data":[7],"are":[8,101,114],"jointly":[9],"characterized":[10],"by":[11,103,170],"its":[12,148],"nonlinear":[13],"temporal":[14,69],"dependencies":[15,100,113],"and":[16,72,110,132,164,176],"complex":[17],"variable":[18,44,52,65,77,83,94,99,112,120,173],"dependencies,":[19],"making":[20],"unsupervised":[21,58],"anomaly":[24,60,149,157,168],"detection":[25,158],"a":[26,51,64,68,73,82,124],"challenging":[27],"task.":[28],"Existing":[29],"methods":[30],"primarily":[31],"rely":[32],"on":[33,81,154,180],"prediction":[34],"or":[35],"reconstruction":[36,74,142],"errors,":[37],"neglecting":[38],"the":[39,43,92,97,104,119,141,144,172,184],"valuable":[40],"information":[41],"within":[42],"dependencies.":[45],"In":[46],"this":[47,137],"paper,":[48],"we":[49],"propose":[50],"dependency":[53,70,84,121,174],"discrepancy-based":[54],"Transformer":[55],"(VDDFormer)":[56],"for":[57],"MTS":[59],"detection.":[61],"VDDFormer":[62,162],"comprises":[63],"correlation":[66,78,106],"encoder,":[67,71],"decoder.":[75],"encoder":[79],"capitalizes":[80],"attention":[85],"mechanism,":[86],"which":[87],"employs":[88],"self-attention":[89],"to":[90,117,128],"learn":[91],"global":[93,109],"dependencies;":[95],"meanwhile,":[96],"local":[98,111],"captured":[102],"adaptive":[105],"matrix.":[107],"then":[115],"used":[116],"compute":[118],"discrepancy":[122,139,175],"as":[123],"new":[125,138],"intrinsic":[126],"property":[127],"distinguish":[129],"between":[130],"normal":[131],"abnormal":[133],"patterns.":[134],"By":[135],"integrating":[136],"with":[140],"error,":[143],"model":[145],"effectively":[146,163],"enhances":[147],"differentiation":[150],"capability.":[151],"Extensive":[152],"experiments":[153],"five":[155,185],"real-world":[156],"datasets":[159],"demonstrate":[160],"that":[161],"robustly":[165],"detects":[166],"group":[167],"patterns":[169],"leveraging":[171],"achieves":[177],"state-of-the-art":[178],"performance":[179],"four":[181],"out":[182],"datasets.":[186]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}