{"id":"https://openalex.org/W7131642156","doi":"https://doi.org/10.1109/ickg66886.2025.00058","title":"High-Variance Graph Framelets for Heterophilous Graph Learning","display_name":"High-Variance Graph Framelets for Heterophilous Graph Learning","publication_year":2025,"publication_date":"2025-11-13","ids":{"openalex":"https://openalex.org/W7131642156","doi":"https://doi.org/10.1109/ickg66886.2025.00058"},"language":null,"primary_location":{"id":"doi:10.1109/ickg66886.2025.00058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ickg66886.2025.00058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Knowledge Graph (ICKG)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5073952026","display_name":"Ruigang Zheng","orcid":"https://orcid.org/0000-0003-4056-3484"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ruigang Zheng","raw_affiliation_strings":["City University of Hong Kong,Department of Mathematics,Hong Kong,SAR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Mathematics,Hong Kong,SAR China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126453943","display_name":"Ming Li","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["Ministry of Education, Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology,Guilin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology,Guilin,China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126877418","display_name":"Xiaosheng Zhuang","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaosheng Zhuang","raw_affiliation_strings":["City University of Hong Kong,Department of Mathematics,Hong Kong,SAR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Mathematics,Hong Kong,SAR China","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"397","last_page":"403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9128999710083008,"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":0.9128999710083008,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.03420000150799751,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.010200000368058681,"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/graph","display_name":"Graph","score":0.614300012588501},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5232999920845032},{"id":"https://openalex.org/keywords/graph-property","display_name":"Graph property","score":0.45649999380111694},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.44670000672340393},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.40119999647140503},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.39579999446868896},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.38109999895095825}],"concepts":[{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.614300012588501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5234000086784363},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5232999920845032},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5120999813079834},{"id":"https://openalex.org/C64339825","wikidata":"https://www.wikidata.org/wiki/Q722659","display_name":"Graph property","level":5,"score":0.45649999380111694},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.44670000672340393},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C2780022179","wikidata":"https://www.wikidata.org/wiki/Q1986794","display_name":"Molecular graph","level":3,"score":0.3068000078201294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29440000653266907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28619998693466187},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C136979486","wikidata":"https://www.wikidata.org/wiki/Q773483","display_name":"Existential quantification","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ickg66886.2025.00058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ickg66886.2025.00058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Knowledge Graph (ICKG)","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":10,"referenced_works":["https://openalex.org/W122561819","https://openalex.org/W2132984323","https://openalex.org/W2907492528","https://openalex.org/W2964051675","https://openalex.org/W3130546334","https://openalex.org/W3133473108","https://openalex.org/W3212660021","https://openalex.org/W4392796768","https://openalex.org/W4393972734","https://openalex.org/W4409364207"],"related_works":[],"abstract_inverted_index":{"Heterophilous":[0],"graphs":[1],"are":[2,70,77],"characterized":[3],"by":[4,45],"connections":[5],"predominantly":[6],"occurring":[7],"between":[8],"nodes":[9],"of":[10,39,64,88,139,146],"differing":[11],"classes,":[12],"resulting":[13],"in":[14,55,91,166],"highly":[15,79],"non-smooth":[16],"or":[17,106],"\u201chighly":[18],"varying\u201d":[19],"label":[20,40],"distributions":[21],"across":[22],"the":[23,37,46,52,83,137,144],"graph.":[24],"This":[25,150],"structural":[26],"property":[27],"challenges":[28,145],"conventional":[29],"graph":[30,66,125,148],"learning":[31],"methods,":[32,164],"which":[33],"often":[34],"rely":[35],"on":[36,121],"assumption":[38],"and":[41,85,160],"feature":[42,74],"smoothness.":[43],"Motivated":[44],"need":[47],"to":[48,72,116,172],"better":[49],"align":[50],"with":[51],"intrinsic":[53],"heterophily":[54],"such":[56],"graphs,":[57],"we":[58],"propose":[59],"a":[60,111],"general":[61],"parameterized":[62],"system":[63],"high-variance":[65,96,140],"framelets.":[67],"These":[68],"framelets":[69,97],"designed":[71],"generate":[73],"representations":[75,141],"that":[76,128],"themselves":[78],"varying,":[80],"thereby":[81],"enhancing":[82],"expressiveness":[84],"discriminative":[86],"power":[87],"node":[89,133],"features":[90],"heterophilous":[92,124,147],"settings.":[93],"The":[94],"proposed":[95],"can":[98],"be":[99],"flexibly":[100],"constructed":[101],"without":[102],"requiring":[103],"data":[104],"leakage":[105],"task-specific":[107],"training,":[108],"making":[109],"them":[110],"lightweight":[112],"yet":[113],"effective":[114],"addition":[115],"existing":[117],"models.":[118],"Experimental":[119],"results":[120],"two":[122],"representative":[123],"datasets":[126],"demonstrate":[127],"our":[129],"method":[130],"consistently":[131],"improves":[132],"classification":[134],"accuracy,":[135],"highlighting":[136],"potential":[138],"for":[142,156],"addressing":[143],"learning.":[149],"work":[151],"opens":[152],"up":[153],"promising":[154],"avenues":[155],"developing":[157],"more":[158],"adaptive":[159],"theoretically":[161],"grounded":[162],"spectral":[163],"particularly":[165],"settings":[167],"where":[168],"smoothness":[169],"assumptions":[170],"fail":[171],"hold.":[173]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-27T00:00:00"}
