{"id":"https://openalex.org/W4414360060","doi":"https://doi.org/10.24963/ijcai.2025/349","title":"DGExplainer: Explaining Dynamic Graph Neural Networks via Relevance Back-propagation","display_name":"DGExplainer: Explaining Dynamic Graph Neural Networks via Relevance Back-propagation","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360060","doi":"https://doi.org/10.24963/ijcai.2025/349"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/349","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5024225991","display_name":"Yezi Liu","orcid":"https://orcid.org/0000-0003-0454-5238"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yezi Liu","raw_affiliation_strings":["University of California, Irvine"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Irvine","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020017704","display_name":"Jiaxuan Xie","orcid":"https://orcid.org/0009-0009-6920-7804"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaxuan Xie","raw_affiliation_strings":["University of California, Irvine"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Irvine","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019337064","display_name":"Yanning Shen","orcid":"https://orcid.org/0000-0002-7333-893X"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanning Shen","raw_affiliation_strings":["University of California, Irvine"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Irvine","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024225991"],"corresponding_institution_ids":["https://openalex.org/I204250578"],"apc_list":null,"apc_paid":null,"fwci":2.1406,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90337123,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3135","last_page":"3143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9865000247955322,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9865000247955322,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9781000018119812,"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/T10028","display_name":"Topic Modeling","score":0.9753999710083008,"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/relevance","display_name":"Relevance (law)","score":0.8187999725341797},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5472999811172485},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5109999775886536},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.46299999952316284},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46209999918937683},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.357699990272522},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.32670000195503235}],"concepts":[{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.8187999725341797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7662000060081482},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.46299999952316284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46209999918937683},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45419999957084656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44359999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4097999930381775},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39809998869895935},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C197298091","wikidata":"https://www.wikidata.org/wiki/Q5318963","display_name":"Dynamic data","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C2776800370","wikidata":"https://www.wikidata.org/wiki/Q5172864","display_name":"Correlative","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/349","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Dynamic":[0],"graph":[1,99],"neural":[2],"networks":[3],"(dynamic":[4],"GNNs)":[5],"have":[6,48],"demonstrated":[7],"remarkable":[8],"effectiveness":[9,181],"in":[10,39,184,194],"analyzing":[11],"time-varying":[12],"graph-structured":[13],"data.":[14],"However,":[15],"their":[16,24,29,70],"black-box":[17],"nature":[18],"often":[19],"hinders":[20],"users":[21],"from":[22,155],"understanding":[23],"predictions,":[25],"which":[26,108],"can":[27],"limit":[28],"applications.":[30],"In":[31],"recent":[32],"years,":[33],"there":[34],"has":[35],"been":[36],"a":[37,65,77,110,156],"surge":[38],"research":[40],"aimed":[41],"at":[42],"explaining":[43,83],"GNNs,":[44],"but":[45],"most":[46],"studies":[47],"focused":[49],"on":[50,175],"static":[51,84],"graphs,":[52],"leaving":[53],"the":[54,119,134,140,143,161,167,180],"explanation":[55,112],"of":[56,113,136,142,163,182],"dynamic":[57,62,91,114,195],"GNNs":[58,63],"relatively":[59],"unexplored.":[60],"Explaining":[61],"presents":[64],"unique":[66],"challenge":[67],"due":[68],"to":[69,90],"complex":[71],"spatial":[72],"and":[73,125,171,191],"temporal":[74,96,130],"structures.":[75],"As":[76],"result,":[78],"existing":[79],"approaches":[80],"designed":[81],"for":[82,147,188],"graphs":[85,92],"are":[86],"not":[87],"directly":[88],"applicable":[89],"because":[93],"they":[94],"ignore":[95],"dependencies":[97],"among":[98],"snapshots.":[100],"To":[101],"address":[102],"this":[103],"issue,":[104],"we":[105],"propose":[106],"DGExplainer,":[107],"offers":[109],"reliable":[111],"GNN":[115],"predictions.":[116],"DGExplainer":[117,183],"utilizes":[118],"relevance":[120,135,154,162],"back-propagation":[121,168],"technique":[122],"both":[123],"time-wise":[124],"layer-wise.":[126],"Specifically,":[127],"it":[128,151],"incorporates":[129],"information":[131],"by":[132,159],"computing":[133],"node":[137,164,192],"representations":[138,165],"along":[139,166],"inverse":[141],"time":[144,149],"evolution.":[145],"Additionally,":[146],"each":[148],"step,":[150],"calculates":[152],"layer-wise":[153],"graph-based":[157],"module":[158],"redistributing":[160],"path.":[169],"Quantitative":[170],"qualitative":[172],"experimental":[173],"results":[174],"six":[176],"real-world":[177],"datasets":[178],"demonstrate":[179],"identifying":[185],"important":[186],"nodes":[187],"link":[189],"prediction":[190],"regression":[193],"GNNs.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}