{"id":"https://openalex.org/W4381713847","doi":"https://doi.org/10.1109/tnnls.2023.3288484","title":"Structure-Aware DropEdge Toward Deep Graph Convolutional Networks","display_name":"Structure-Aware DropEdge Toward Deep Graph Convolutional Networks","publication_year":2023,"publication_date":"2023-07-26","ids":{"openalex":"https://openalex.org/W4381713847","doi":"https://doi.org/10.1109/tnnls.2023.3288484","pmid":"https://pubmed.ncbi.nlm.nih.gov/37494169"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3288484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3288484","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.12091","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029027880","display_name":"Jiaqi Han","orcid":"https://orcid.org/0000-0003-1786-3817"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Han","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032642601","display_name":"Wenbing Huang","orcid":"https://orcid.org/0000-0002-2566-4159"},"institutions":[{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]},{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbing Huang","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2566-4159","affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I4210096250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767600","display_name":"Yu Rong","orcid":"https://orcid.org/0000-0001-7387-302X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Rong","raw_affiliation_strings":["Tencent AI Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-7387-302X","affiliations":[{"raw_affiliation_string":"Tencent AI Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005345630","display_name":"Tingyang Xu","orcid":"https://orcid.org/0000-0002-8487-9045"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingyang Xu","raw_affiliation_strings":["Tencent AI Laboratory, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055546056","display_name":"Fuchun Sun","orcid":"https://orcid.org/0000-0003-3546-6305"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchun Sun","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3546-6305","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068865316","display_name":"Junzhou Huang","orcid":"https://orcid.org/0000-0002-9548-1227"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junzhou Huang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3569,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.90474954,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"35","issue":"11","first_page":"15565","last_page":"15577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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":0.9991999864578247,"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/T12676","display_name":"Machine Learning and ELM","score":0.9509999752044678,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9462000131607056,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5383393168449402},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4830780327320099},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42286813259124756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4146322011947632},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39556917548179626},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38595423102378845},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34863972663879395},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.34214362502098083},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.09786766767501831}],"concepts":[{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5383393168449402},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4830780327320099},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42286813259124756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4146322011947632},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39556917548179626},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38595423102378845},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34863972663879395},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.34214362502098083},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.09786766767501831}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2023.3288484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3288484","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37494169","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37494169","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:2306.12091","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.12091","pdf_url":"https://arxiv.org/pdf/2306.12091","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2306.12091","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.12091","pdf_url":"https://arxiv.org/pdf/2306.12091","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3265846782","display_name":null,"funder_award_id":"62006137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"},{"id":"https://openalex.org/F4320322499","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381713847.pdf","grobid_xml":"https://content.openalex.org/works/W4381713847.grobid-xml"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W637153065","https://openalex.org/W1662382123","https://openalex.org/W2142124258","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2194775991","https://openalex.org/W2547875792","https://openalex.org/W2558460151","https://openalex.org/W2751808960","https://openalex.org/W2804057010","https://openalex.org/W2809418595","https://openalex.org/W2900470550","https://openalex.org/W2907492528","https://openalex.org/W2947983671","https://openalex.org/W2952029609","https://openalex.org/W2961295589","https://openalex.org/W2962756421","https://openalex.org/W2963017945","https://openalex.org/W2963084622","https://openalex.org/W2963312446","https://openalex.org/W2963695795","https://openalex.org/W2964015378","https://openalex.org/W2964051675","https://openalex.org/W2964145825","https://openalex.org/W2964321699","https://openalex.org/W2975868979","https://openalex.org/W2978508283","https://openalex.org/W2996268457","https://openalex.org/W2998496395","https://openalex.org/W3011900384","https://openalex.org/W3024536663","https://openalex.org/W3034492151","https://openalex.org/W3035659929","https://openalex.org/W3082217026","https://openalex.org/W3104097132","https://openalex.org/W3105136071","https://openalex.org/W3155649272","https://openalex.org/W3158730736","https://openalex.org/W3208390110","https://openalex.org/W3211236454","https://openalex.org/W4210257598","https://openalex.org/W4220825043","https://openalex.org/W4226058932","https://openalex.org/W4226102968","https://openalex.org/W4282925200","https://openalex.org/W4287197019","https://openalex.org/W4288088467","https://openalex.org/W4289389616","https://openalex.org/W4292851012","https://openalex.org/W4294558607","https://openalex.org/W4297571622","https://openalex.org/W4297733535","https://openalex.org/W4313887026","https://openalex.org/W6620673361","https://openalex.org/W6637178625","https://openalex.org/W6699364125","https://openalex.org/W6713582119","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6729448088","https://openalex.org/W6738964360","https://openalex.org/W6743410771","https://openalex.org/W6745537798","https://openalex.org/W6748799445","https://openalex.org/W6752110883","https://openalex.org/W6754030515","https://openalex.org/W6755863455","https://openalex.org/W6756561102","https://openalex.org/W6765543928","https://openalex.org/W6766892243","https://openalex.org/W6767957595","https://openalex.org/W6767998753","https://openalex.org/W6768314895","https://openalex.org/W6771932116","https://openalex.org/W6779477267","https://openalex.org/W6779961489","https://openalex.org/W6782455772","https://openalex.org/W6798862450"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2051487156","https://openalex.org/W2504004674","https://openalex.org/W2073681303","https://openalex.org/W2963177394","https://openalex.org/W2498744856","https://openalex.org/W4390482104","https://openalex.org/W322408318","https://openalex.org/W149041114","https://openalex.org/W1965815883"],"abstract_inverted_index":{"It":[0],"has":[1],"been":[2],"discovered":[3],"that":[4,24,100,152],"graph":[5],"convolutional":[6],"networks":[7],"(GCNs)":[8],"encounter":[9],"a":[10,127,189],"remarkable":[11],"drop":[12],"in":[13,32,82],"performance":[14,110,197],"when":[15],"multiple":[16],"layers":[17],"are":[18],"piled":[19],"up.":[20],"The":[21],"main":[22],"factor":[23],"accounts":[25],"for":[26,77],"why":[27],"deep":[28],"GCNs":[29],"fail":[30],"lies":[31],"oversmoothing,":[33],"which":[34],"isolates":[35],"the":[36,40,43,94,105,112,134,139,144,156,160,164,181,201],"network":[37,46],"output":[38,161],"from":[39,104],"input":[41,165],"with":[42,124,143,163,188],"increase":[44],"of":[45,147,159,183,191],"depth,":[47],"weakening":[48],"expressivity":[49],"and":[50,89,150,177,185,200],"trainability.":[51],"In":[52],"this":[53,122],"article,":[54],"we":[55,97,137],"start":[56],"by":[57,193],"investigating":[58],"refined":[59],"measures":[60],"upon":[61],"DropEdge-an":[62],"existing":[63],"simple":[64],"yet":[65],"effective":[66],"technique":[67],"to":[68,84,131],"relieve":[69],"oversmoothing.":[70,132],"We":[71,119],"term":[72],"our":[73],"method":[74],"as":[75,115,117],"DropEdge++":[76,184],"its":[78,186],"two":[79],"structure-aware":[80],"samplers":[81],"contrast":[83],"DropEdge:":[85],"layer-dependent":[86],"(LD)":[87],"sampler":[88],"feature-dependent":[90],"(FD)":[91],"sampler.":[92],"Regarding":[93],"LD":[95],"sampler,":[96,136],"interestingly":[98],"find":[99],"increasingly":[101],"sampling":[102,141],"edges":[103],"bottom":[106],"layer":[107,162],"yields":[108],"superior":[109],"than":[111],"decreasing":[113],"counterpart":[114],"well":[116],"DropEdge.":[118],"theoretically":[120],"reveal":[121],"phenomenon":[123],"mean-edge-number":[125],"(MEN),":[126],"metric":[128],"closely":[129],"related":[130],"For":[133],"FD":[135],"associate":[138],"edge":[140],"probability":[142],"feature":[145],"similarity":[146],"node":[148,171],"pairs":[149],"prove":[151],"it":[153],"further":[154],"correlates":[155],"convergence":[157],"subspace":[158],"features.":[166],"Extensive":[167],"experiments":[168],"on":[169],"several":[170],"classification":[172],"benchmarks,":[173],"including":[174],"both":[175],"full-":[176],"semi-supervised":[178],"tasks,":[179],"illustrate":[180],"efficacy":[182],"compatibility":[187],"variety":[190],"backbones":[192],"achieving":[194],"generally":[195],"better":[196],"over":[198],"DropEdge":[199],"no-drop":[202],"version.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}