{"id":"https://openalex.org/W4411724790","doi":"https://doi.org/10.1109/iscas56072.2025.11043617","title":"TWavefussion: Wavelet-based Diffusion with Transformer for Multivariate Time Series Anomaly Detection","display_name":"TWavefussion: Wavelet-based Diffusion with Transformer for Multivariate Time Series Anomaly Detection","publication_year":2025,"publication_date":"2025-05-25","ids":{"openalex":"https://openalex.org/W4411724790","doi":"https://doi.org/10.1109/iscas56072.2025.11043617"},"language":"en","primary_location":{"id":"doi:10.1109/iscas56072.2025.11043617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas56072.2025.11043617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-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/A5109256566","display_name":"H. Y. Sheng","orcid":"https://orcid.org/0009-0008-0575-0798"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Hongjun Sheng","raw_affiliation_strings":["Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020477816","display_name":"Xinggan Peng","orcid":"https://orcid.org/0000-0002-1087-8576"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinggan Peng","raw_affiliation_strings":["CMCU Engineering Co., Ltd,Chongqing,China,400039"],"affiliations":[{"raw_affiliation_string":"CMCU Engineering Co., Ltd,Chongqing,China,400039","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092843978","display_name":"Van Kwan Zhi Koh","orcid":"https://orcid.org/0000-0002-6207-4692"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Van Kwan Zhi Koh","raw_affiliation_strings":["Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024709593","display_name":"Bihan Wen","orcid":"https://orcid.org/0000-0002-6874-6453"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Bihan Wen","raw_affiliation_strings":["Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083558550","display_name":"Zhiping Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhiping Lin","raw_affiliation_strings":["Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical and Electronic Engineering,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109256566"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08154506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.9988999962806702,"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":0.9988999962806702,"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":0.9854999780654907,"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":0.9426000118255615,"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/multivariate-statistics","display_name":"Multivariate statistics","score":0.6017919182777405},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.595765233039856},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.577061116695404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.549299955368042},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5449144244194031},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5276497602462769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3999128043651581},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39916032552719116},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35160669684410095},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1586567461490631},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1378585696220398}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6017919182777405},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.595765233039856},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.577061116695404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.549299955368042},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5449144244194031},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5276497602462769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3999128043651581},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39916032552719116},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35160669684410095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1586567461490631},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1378585696220398},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas56072.2025.11043617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas56072.2025.11043617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2604247107","https://openalex.org/W2790344751","https://openalex.org/W2833324965","https://openalex.org/W2911200746","https://openalex.org/W2948517885","https://openalex.org/W2950361482","https://openalex.org/W3153890562","https://openalex.org/W3169450514","https://openalex.org/W3170981104","https://openalex.org/W3204937802","https://openalex.org/W3213388407","https://openalex.org/W4323322022","https://openalex.org/W4384947601","https://openalex.org/W4392903168","https://openalex.org/W4395090230","https://openalex.org/W4400231673","https://openalex.org/W4402626814"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2406638334","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Multivariate":[0],"Time":[1],"Series":[2],"(MTS)":[3],"anomaly":[4,49,61],"detection":[5,62],"is":[6,70],"challenging":[7],"in":[8,15,33,47,80],"distinguishing":[9],"anomalous":[10],"data":[11,14],"from":[12],"normal":[13],"high-dimensional,":[16],"complex":[17],"distributions.":[18],"Even":[19],"some":[20],"deep":[21],"learning":[22],"methods":[23],"still":[24],"have":[25,40],"difficulties":[26],"capturing":[27],"intricate":[28],"MTS":[29,48,60,94],"patterns.":[30],"Recent":[31],"advancements":[32],"Diffusion":[34],"Models":[35],"(DM)":[36],"for":[37,59],"sample":[38],"generation":[39],"inspired":[41],"us":[42],"to":[43],"explore":[44],"their":[45],"potential":[46],"detection.":[50],"In":[51],"this":[52],"paper,":[53],"TWavefussion,":[54],"an":[55],"unsupervised":[56],"diffusion":[57,65,74],"model":[58,66,75],"combining":[63],"wavelet-based":[64,73],"and":[67,87,92],"transformer":[68],"autoencoder,":[69],"proposed.":[71],"The":[72],"captures":[76],"fine-grained":[77],"local":[78,91],"features":[79,86,95],"the":[81],"high-frequency":[82],"components":[83],"of":[84,106],"latent":[85],"helps":[88],"fuse":[89],"both":[90],"global":[93],"better.":[96],"Comparative":[97],"experiments":[98],"show":[99],"TWavefussion":[100],"achieves":[101],"leading":[102],"performance":[103],"on":[104],"three":[105],"four":[107],"datasets.":[108]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}