{"id":"https://openalex.org/W4414966536","doi":"https://doi.org/10.3390/a18100632","title":"TRed-GNN: A Robust Graph Neural Network with Task-Relevant Edge Disentanglement and Reverse Process Mechanism","display_name":"TRed-GNN: A Robust Graph Neural Network with Task-Relevant Edge Disentanglement and Reverse Process Mechanism","publication_year":2025,"publication_date":"2025-10-08","ids":{"openalex":"https://openalex.org/W4414966536","doi":"https://doi.org/10.3390/a18100632"},"language":"en","primary_location":{"id":"doi:10.3390/a18100632","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18100632","pdf_url":"https://www.mdpi.com/1999-4893/18/10/632/pdf?version=1759915973","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/18/10/632/pdf?version=1759915973","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088958306","display_name":"Menghui Xu","orcid":"https://orcid.org/0000-0003-3906-1129"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Menghui Xu","raw_affiliation_strings":["School of Artificial Intelligence, Tiangong University, Tianjin 300387, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Tiangong University, Tianjin 300387, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103233342","display_name":"Yan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I133270356","display_name":"Tianjin University of Technology and Education","ror":"https://ror.org/035gwtk09","country_code":"CN","type":"education","lineage":["https://openalex.org/I133270356"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Yan","raw_affiliation_strings":["School of Information Technology and Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"],"affiliations":[{"raw_affiliation_string":"School of Information Technology and Engineering, Tianjin University of Technology and Education, Tianjin 300222, China","institution_ids":["https://openalex.org/I133270356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101795819","display_name":"Qiuyan Wang","orcid":"https://orcid.org/0000-0001-5951-9219"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]},{"id":"https://openalex.org/I64449678","display_name":"Putian University","ror":"https://ror.org/00jmsxk74","country_code":"CN","type":"education","lineage":["https://openalex.org/I64449678"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuyan Wang","raw_affiliation_strings":["Fujian Key Laboratory of Financial Information Processing, Putian University, Putian 351100, China","School of Computer Science and Technology, Tiangong University, Tianjin 300387, China"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Financial Information Processing, Putian University, Putian 351100, China","institution_ids":["https://openalex.org/I64449678"]},{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin 300387, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040624202","display_name":"Hanning Chen","orcid":"https://orcid.org/0000-0003-3568-8039"},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]},{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanning Chen","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin 300457, China","School of Artificial Intelligence, Tiangong University, Tianjin 300387, China"],"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin 300457, China","institution_ids":["https://openalex.org/I132369690"]},{"raw_affiliation_string":"School of Artificial Intelligence, Tiangong University, Tianjin 300387, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102224436","display_name":"Zhao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Zhang","raw_affiliation_strings":["College of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin 300457, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin 300457, China","institution_ids":["https://openalex.org/I132369690"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5040624202","https://openalex.org/A5103233342"],"corresponding_institution_ids":["https://openalex.org/I132369690","https://openalex.org/I133270356","https://openalex.org/I198091727"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14936855,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"10","first_page":"632","last_page":"632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11948","display_name":"Machine Learning in Materials Science","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5843999981880188},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5343999862670898},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5153999924659729},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4320000112056732},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.42250001430511475},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.4147999882698059},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4115999937057495},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.3905999958515167},{"id":"https://openalex.org/keywords/homophily","display_name":"Homophily","score":0.3901999890804291}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621999979019165},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5843999981880188},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5153999924659729},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4587000012397766},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4320000112056732},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39800000190734863},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3903999924659729},{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35440000891685486},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30649998784065247},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C2780600066","wikidata":"https://www.wikidata.org/wiki/Q7239828","display_name":"Preferential attachment","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.2635999917984009},{"id":"https://openalex.org/C56951928","wikidata":"https://www.wikidata.org/wiki/Q3539213","display_name":"Trimming","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a18100632","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18100632","pdf_url":"https://www.mdpi.com/1999-4893/18/10/632/pdf?version=1759915973","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fde67b9858274d278861e48715954758","is_oa":true,"landing_page_url":"https://doaj.org/article/fde67b9858274d278861e48715954758","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 18, Iss 10, p 632 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a18100632","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18100632","pdf_url":"https://www.mdpi.com/1999-4893/18/10/632/pdf?version=1759915973","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320326529","display_name":"Putian University","ror":"https://ror.org/00jmsxk74"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414966536.pdf"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2998324911","https://openalex.org/W2998496395","https://openalex.org/W3090999459","https://openalex.org/W3093410149","https://openalex.org/W3100646853","https://openalex.org/W3116239416","https://openalex.org/W3128443161","https://openalex.org/W3153206160","https://openalex.org/W3154497962","https://openalex.org/W3211849317","https://openalex.org/W3212660021","https://openalex.org/W4210696851","https://openalex.org/W4225977739","https://openalex.org/W4287115771","https://openalex.org/W4295934584","https://openalex.org/W4306705227","https://openalex.org/W4312083502","https://openalex.org/W4365790993","https://openalex.org/W4379743834","https://openalex.org/W4387340007","https://openalex.org/W4388183174","https://openalex.org/W4389148664","https://openalex.org/W4401836381","https://openalex.org/W4402473812"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"capture":[4],"complex":[5],"information":[6,154],"in":[7],"graph-structured":[8],"data":[9],"by":[10],"integrating":[11],"node":[12,100],"features":[13,128],"with":[14],"iterative":[15],"updates":[16],"of":[17,29,52,99,136],"graph":[18,111,203],"topology.":[19,131],"However,":[20],"they":[21],"inherently":[22],"rely":[23],"on":[24,77,102,175,192],"the":[25,30,95,109,134,148,156],"homophily":[26],"assumption\u2014that":[27],"nodes":[28,51],"same":[31],"class":[32],"tend":[33],"to":[34,74,92,125,168,189],"form":[35],"edges.":[36],"In":[37,80],"contrast,":[38],"real-world":[39,177],"networks":[40],"often":[41],"exhibit":[42],"heterophilous":[43,78,103],"structures,":[44],"where":[45],"edges":[46],"are":[47],"frequently":[48],"formed":[49],"between":[50],"different":[53],"classes.":[54],"Consequently,":[55],"conventional":[56],"GNNs,":[57],"which":[58],"apply":[59],"uniform":[60],"smoothing":[61],"over":[62],"all":[63],"nodes,":[64],"may":[65],"inadvertently":[66],"aggregate":[67,127],"both":[68,94],"task-relevant":[69,114],"and":[70,97,116,120,166,172,200,206],"task-irrelevant":[71,118,137,157],"information,":[72,138],"leading":[73],"suboptimal":[75],"performance":[76,96,187],"graphs.":[79,104],"this":[81],"work,":[82],"we":[83,139],"propose":[84],"TRed-GNN,":[85],"a":[86,113,117,122,141],"novel":[87],"end-to-end":[88],"GNN":[89],"architecture":[90],"designed":[91],"enhance":[93],"robustness":[98],"classification":[101,186],"The":[105],"proposed":[106],"approach":[107],"decomposes":[108],"original":[110],"into":[112],"subgraph":[115,119,158],"employs":[121],"dual-channel":[123],"mechanism":[124,144],"independently":[126],"from":[129,155],"each":[130],"To":[132],"mitigate":[133],"interference":[135],"introduce":[140],"reverse":[142],"process":[143],"that,":[145],"without":[146],"compromising":[147],"main":[149],"task,":[150],"extracts":[151],"potentially":[152],"useful":[153],"while":[159],"filtering":[160],"out":[161],"noise,":[162],"thereby":[163],"improving":[164],"generalization":[165],"resilience":[167],"perturbations.":[169],"Theoretical":[170],"analysis":[171],"extensive":[173],"experiments":[174],"multiple":[176],"datasets":[178],"demonstrate":[179],"that":[180],"TRed-GNN":[181],"not":[182],"only":[183],"achieves":[184],"superior":[185],"compared":[188],"existing":[190],"methods":[191],"most":[193],"benchmarks,":[194],"but":[195],"also":[196],"exhibits":[197],"strong":[198],"adaptability":[199],"stability":[201],"under":[202],"structural":[204],"perturbations":[205],"over-smoothing":[207],"scenarios.":[208]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
