{"id":"https://openalex.org/W4414558811","doi":"https://doi.org/10.1142/s0218001425520263","title":"A Structural Change Detection Method Integrating Causal Inference and Deep Learning","display_name":"A Structural Change Detection Method Integrating Causal Inference and Deep Learning","publication_year":2025,"publication_date":"2025-09-27","ids":{"openalex":"https://openalex.org/W4414558811","doi":"https://doi.org/10.1142/s0218001425520263"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001425520263","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001425520263","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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":null,"display_name":"Tong Liu","orcid":"https://orcid.org/0009-0009-7780-2646"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tong Liu","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong 999007, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0009-0009-7780-2646","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong 999007, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hualin Liu","orcid":"https://orcid.org/0000-0001-5476-2228"},"institutions":[{"id":"https://openalex.org/I37448385","display_name":"China People's Public Security University","ror":"https://ror.org/05twya590","country_code":"CN","type":"education","lineage":["https://openalex.org/I37448385"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hualin Liu","raw_affiliation_strings":["People\u2019s Public Security University of China, Beijing 100038, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0000-0001-5476-2228","affiliations":[{"raw_affiliation_string":"People\u2019s Public Security University of China, Beijing 100038, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I37448385"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.13216964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"39","issue":"16","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.399399995803833,"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":0.399399995803833,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.6833999752998352},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6068999767303467},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5419999957084656},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.5304999947547913},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4871000051498413},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47540000081062317},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4503999948501587},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44440001249313354},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.43700000643730164}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7450000047683716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067000269889832},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.6833999752998352},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6068999767303467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5419999957084656},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5419999957084656},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.5304999947547913},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4871000051498413},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4503999948501587},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3361999988555908},{"id":"https://openalex.org/C61665672","wikidata":"https://www.wikidata.org/wiki/Q303100","display_name":"Graph isomorphism","level":4,"score":0.329800009727478},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C203436722","wikidata":"https://www.wikidata.org/wiki/Q902950","display_name":"Isomorphism (crystallography)","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001425520263","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001425520263","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1544178588","https://openalex.org/W1965555277","https://openalex.org/W1975684011","https://openalex.org/W2009494091","https://openalex.org/W2022851810","https://openalex.org/W2073307618","https://openalex.org/W2074812030","https://openalex.org/W2110015307","https://openalex.org/W2169347809","https://openalex.org/W2395172628","https://openalex.org/W2396881363","https://openalex.org/W2593118993","https://openalex.org/W2755310417","https://openalex.org/W3162776190","https://openalex.org/W4248735994","https://openalex.org/W4249116379","https://openalex.org/W4390116356"],"related_works":[],"abstract_inverted_index":{"To":[0,55],"accurately":[1],"detect":[2],"structural":[3,59,101,157],"changes":[4,110],"driven":[5],"by":[6],"shifts":[7],"in":[8,111,155],"underlying":[9],"causal":[10,23,34,43,51,80,89,114],"mechanisms,":[11],"we":[12],"propose":[13],"CaSCo":[14,29,98,147],"(Causal":[15],"Structure":[16],"Comparison),":[17],"a":[18,32,64,100],"novel":[19],"framework":[20,117],"that":[21,105,146],"integrates":[22],"inference":[24],"with":[25],"deep":[26,152],"representation":[27],"learning.":[28],"first":[30],"leverages":[31],"differentiable":[33],"structure":[35],"learning":[36],"method":[37],"based":[38],"on":[39,139],"NOTEARS":[40],"to":[41,77,125],"construct":[42],"graphs":[44,81],"from":[45],"observational":[46],"data,":[47],"uncovering":[48],"the":[49,87,112],"latent":[50],"dependencies":[52],"among":[53],"variables.":[54],"capture":[56],"subtle":[57],"local":[58],"variations":[60],"and":[61,120,133,142,151,163],"nonlinear":[62],"patterns,":[63],"graph":[65],"neural":[66],"network":[67],"(GNN)":[68],"using":[69],"Graph":[70],"Isomorphism":[71],"Network":[72],"(GIN)":[73],"architecture":[74],"is":[75,118],"employed":[76],"encode":[78],"these":[79],"into":[82],"expressive":[83],"embeddings.":[84],"By":[85],"comparing":[86],"learned":[88],"representations":[90],"across":[91],"different":[92],"time":[93],"windows":[94],"or":[95,108],"data":[96],"segments,":[97],"introduces":[99],"change":[102],"scoring":[103],"mechanism":[104],"identifies":[106],"abrupt":[107],"gradual":[109],"system\u2019s":[113],"dynamics.":[115],"The":[116],"general":[119],"scalable,":[121],"making":[122],"it":[123],"applicable":[124],"tasks":[126],"such":[127],"as":[128],"time-series":[129],"monitoring,":[130],"anomaly":[131],"detection,":[132],"system":[134],"migration":[135],"analysis.":[136],"Extensive":[137],"experiments":[138],"both":[140],"synthetic":[141],"real-world":[143],"datasets":[144],"demonstrate":[145],"outperforms":[148],"existing":[149],"statistical":[150],"learning-based":[153],"approaches":[154],"detecting":[156],"changes,":[158],"particularly":[159],"under":[160],"nonstationary":[161],"environments":[162],"high-dimensional":[164],"conditions.":[165]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
