{"id":"https://openalex.org/W4385562704","doi":"https://doi.org/10.1145/3580305.3599334","title":"Enhancing Graph Representations Learning with Decorrelated Propagation","display_name":"Enhancing Graph Representations Learning with Decorrelated Propagation","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385562704","doi":"https://doi.org/10.1145/3580305.3599334"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599334","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5101413338","display_name":"Hua Liu","orcid":"https://orcid.org/0000-0002-9613-8877"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Hua Liu","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101837991","display_name":"Haoyu Han","orcid":"https://orcid.org/0000-0002-2529-6042"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoyu Han","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100758371","display_name":"Wei Jin","orcid":"https://orcid.org/0000-0002-5054-954X"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Jin","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100621795","display_name":"Xiaorui Liu","orcid":"https://orcid.org/0000-0001-8217-5688"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaorui Liu","raw_affiliation_strings":["North Carolina State University, Raleigh, NC, USA"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101566727","display_name":"Hui Liu","orcid":"https://orcid.org/0009-0007-9389-7038"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Hui Liu","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101413338"],"corresponding_institution_ids":["https://openalex.org/I154099455","https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":1.2178,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83195087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1466","last_page":"1476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9728999733924866,"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/decorrelation","display_name":"Decorrelation","score":0.7929456233978271},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7109842896461487},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6047110557556152},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5846005082130432},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5614176988601685},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5573369264602661},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5151623487472534},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4777316749095917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4707249701023102},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36324620246887207},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33696335554122925},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.325560986995697},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25719860196113586},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14463484287261963}],"concepts":[{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.7929456233978271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109842896461487},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6047110557556152},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5846005082130432},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5614176988601685},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5573369264602661},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5151623487472534},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4777316749095917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4707249701023102},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36324620246887207},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33696335554122925},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.325560986995697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25719860196113586},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14463484287261963},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599334","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W317957491","https://openalex.org/W2155201359","https://openalex.org/W2194775991","https://openalex.org/W2593110912","https://openalex.org/W2807021761","https://openalex.org/W2907492528","https://openalex.org/W2998496395","https://openalex.org/W3009901425","https://openalex.org/W3042770487","https://openalex.org/W3099064659","https://openalex.org/W3099375322","https://openalex.org/W3100848837","https://openalex.org/W3152560880","https://openalex.org/W3175164304","https://openalex.org/W3201087642","https://openalex.org/W3208180646","https://openalex.org/W3213589113","https://openalex.org/W4284704639","https://openalex.org/W4306316998","https://openalex.org/W4320060387","https://openalex.org/W6804077179"],"related_works":["https://openalex.org/W2382607599","https://openalex.org/W4287995534","https://openalex.org/W2998168123","https://openalex.org/W2400519873","https://openalex.org/W2592385986","https://openalex.org/W2944661354","https://openalex.org/W2573334707","https://openalex.org/W2905846897","https://openalex.org/W2546942002","https://openalex.org/W2970216048"],"abstract_inverted_index":{"In":[0,66,95],"recent":[1,37],"years,":[2],"graph":[3],"neural":[4],"networks":[5],"(GNNs)":[6],"have":[7],"been":[8],"widely":[9],"used":[10,181],"in":[11,19,64,76,89,142],"many":[12],"domains":[13],"due":[14],"to":[15,119,137,170,182],"their":[16],"powerful":[17],"capability":[18],"representation":[20,55],"learning":[21,141],"on":[22,32,155,194],"graph-structured":[23],"data.":[24],"While":[25],"a":[26,46,110,128,134],"majority":[27],"of":[28,43,74,108],"extant":[29],"studies":[30],"focus":[31],"mitigating":[33],"the":[34,41,53,72,86,92,123,139,150],"over-smoothing":[35,184],"problem,":[36,125],"works":[38],"also":[39],"reveal":[40],"limitation":[42],"GNN":[44,143],"from":[45],"new":[47],"over-correlation":[48,75,124,186],"perspective":[49],"which":[50,145],"states":[51],"that":[52,85,102,160,177],"learned":[54],"becomes":[56],"highly":[57],"correlated":[58],"after":[59],"feature":[60,93,112,140,147,196],"transformation":[61],"and":[62,81,185,189],"propagation":[63,87,130,151],"GNNs.":[65],"this":[67],"paper,":[68],"we":[69,97,126,175],"thoroughly":[70],"re-examine":[71],"issue":[73],"deep":[77],"GNNs,":[78,168],"both":[79],"empirically":[80],"theoretically.":[82],"We":[83],"demonstrate":[84,159],"operator":[88],"GNNs":[90],"exacerbates":[91],"correlation.":[94],"addition,":[96],"discovered":[98],"through":[99],"empirical":[100],"study":[101],"existing":[103],"decorrelation":[104,148],"solutions":[105],"fall":[106],"short":[107],"maintaining":[109],"low":[111],"correlation,":[113],"potentially":[114],"encoding":[115],"redundant":[116],"information.":[117],"Thus,":[118],"more":[120],"effectively":[121],"address":[122],"propose":[127],"decorrelated":[129],"scheme":[131],"(DeProp)":[132],"as":[133],"fundamental":[135],"component":[136],"decorrelate":[138],"models,":[144],"achieves":[146],"at":[149,202],"step.":[152],"Comprehensive":[153],"experiments":[154],"multiple":[156],"real-world":[157],"datasets":[158],"DeProp":[161],"can":[162,179],"be":[163,180],"easily":[164],"integrated":[165],"into":[166],"prevalent":[167],"leading":[169],"significant":[171],"performance":[172],"enhancements.":[173],"Furthermore,":[174],"find":[176],"it":[178],"solve":[183],"problems":[187],"simultaneously":[188],"significantly":[190],"outperform":[191],"state-of-the-art":[192],"methods":[193],"missing":[195],"settings.":[197],"The":[198],"code":[199],"is":[200],"available":[201],"https://github.com/hualiu829/DeProp.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
