{"id":"https://openalex.org/W3205090419","doi":"https://doi.org/10.1109/icassp43922.2022.9746838","title":"Label Propagation Across Graphs: Node Classification Using Graph Neural Tangent Kernels","display_name":"Label Propagation Across Graphs: Node Classification Using Graph Neural Tangent Kernels","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W3205090419","doi":"https://doi.org/10.1109/icassp43922.2022.9746838","mag":"3205090419"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746838","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5052572859","display_name":"Artun Bayer","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Artun Bayer","raw_affiliation_strings":["Rice University,Electrical and Computer Engineering,USA","Electrical and Computer Engineering, Rice University, USA"],"affiliations":[{"raw_affiliation_string":"Rice University,Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Rice University, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059527667","display_name":"Arindam Chowdhury","orcid":"https://orcid.org/0000-0001-7298-1969"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arindam Chowdhury","raw_affiliation_strings":["Rice University,Electrical and Computer Engineering,USA","Electrical and Computer Engineering, Rice University, USA"],"affiliations":[{"raw_affiliation_string":"Rice University,Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Rice University, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012007074","display_name":"Santiago Segarra","orcid":"https://orcid.org/0000-0002-8408-9633"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Santiago Segarra","raw_affiliation_strings":["Rice University,Electrical and Computer Engineering,USA","Electrical and Computer Engineering, Rice University, USA"],"affiliations":[{"raw_affiliation_string":"Rice University,Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Rice University, USA","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052572859"],"corresponding_institution_ids":["https://openalex.org/I74775410"],"apc_list":null,"apc_paid":null,"fwci":0.5197,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.60681965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5483","last_page":"5487"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9713000059127808,"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/computer-science","display_name":"Computer science","score":0.683776319026947},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6403890252113342},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5890094041824341},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5037745833396912},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4961460530757904},{"id":"https://openalex.org/keywords/topological-graph-theory","display_name":"Topological graph theory","score":0.47673165798187256},{"id":"https://openalex.org/keywords/tangent","display_name":"Tangent","score":0.4563002288341522},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4229840636253357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41351115703582764},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3891470432281494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24593117833137512},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.19318631291389465},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.17390403151512146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.683776319026947},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6403890252113342},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5890094041824341},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5037745833396912},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4961460530757904},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.47673165798187256},{"id":"https://openalex.org/C138187205","wikidata":"https://www.wikidata.org/wiki/Q131251","display_name":"Tangent","level":2,"score":0.4563002288341522},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4229840636253357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41351115703582764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3891470432281494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24593117833137512},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.19318631291389465},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.17390403151512146},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746838","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1535589824","https://openalex.org/W1955857676","https://openalex.org/W2048053208","https://openalex.org/W2070232376","https://openalex.org/W2101491865","https://openalex.org/W2168029744","https://openalex.org/W2194775991","https://openalex.org/W2487770199","https://openalex.org/W2523246573","https://openalex.org/W2541674938","https://openalex.org/W2766453196","https://openalex.org/W2786915849","https://openalex.org/W2796431263","https://openalex.org/W2809090039","https://openalex.org/W2907492528","https://openalex.org/W2942052807","https://openalex.org/W2944538680","https://openalex.org/W2946985165","https://openalex.org/W2962767366","https://openalex.org/W2963410064","https://openalex.org/W2963695795","https://openalex.org/W2964015378","https://openalex.org/W2966445777","https://openalex.org/W2970474218","https://openalex.org/W2971043187","https://openalex.org/W2971865858","https://openalex.org/W2978508283","https://openalex.org/W2994097903","https://openalex.org/W2995914187","https://openalex.org/W3011667710","https://openalex.org/W3035356236","https://openalex.org/W3101749733","https://openalex.org/W3102554291","https://openalex.org/W3126138172","https://openalex.org/W3132103835","https://openalex.org/W3152787073","https://openalex.org/W3157805807","https://openalex.org/W3162402566","https://openalex.org/W3170945223","https://openalex.org/W4210257598","https://openalex.org/W4287325395","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W6726873649","https://openalex.org/W6727249380","https://openalex.org/W6729059855","https://openalex.org/W6738964360","https://openalex.org/W6748799445","https://openalex.org/W6752495264","https://openalex.org/W6757078134","https://openalex.org/W6761496057","https://openalex.org/W6762944615","https://openalex.org/W6763152702","https://openalex.org/W6768314895","https://openalex.org/W6774527605","https://openalex.org/W6790188306","https://openalex.org/W6790938226","https://openalex.org/W6795142608"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385","https://openalex.org/W2357523926"],"abstract_inverted_index":{"Graph":[0],"neural":[1,143],"networks":[2],"(GNNs)":[3],"have":[4,51],"achieved":[5],"superior":[6],"performance":[7,184],"on":[8,53,162,186],"node":[9,168],"classification":[10],"tasks":[11],"in":[12,21,45,158],"the":[13,28,33,54,59,91,109,113,164,167,172,175],"last":[14],"few":[15],"years.":[16],"Commonly,":[17],"this":[18,70],"is":[19,40,65,95,124],"framed":[20],"a":[22,63,76,81,127,141],"transductive":[23],"semi-supervised":[24],"learning":[25],"setup":[26],"wherein":[27],"entire":[29],"graph":[30,64,94,142],"\u2013":[31,39],"including":[32],"target":[34,93],"nodes":[35,157],"to":[36,125,132,149,153],"be":[37],"labeled":[38,60,84,104],"available":[41,66,87],"for":[42,67,88],"training.":[43,68],"Driven":[44],"part":[46],"by":[47],"scalability,":[48],"recent":[49],"works":[50],"focused":[52],"inductive":[55,78],"case":[56],"where":[57,80],"only":[58],"portion":[61],"of":[62,83,174],"In":[69],"context,":[71],"our":[72,122],"current":[73],"work":[74],"considers":[75],"challenging":[77],"setting":[79],"set":[82],"graphs":[85,117,160],"are":[86,100],"training":[89,116],"while":[90],"unlabeled":[92,106],"completely":[96],"separate,":[97],"i.e.,":[98],"there":[99],"no":[101],"connections":[102,179],"between":[103,156],"and":[105,115,166,180],"nodes.":[107],"Under":[108],"implicit":[110],"assumption":[111],"that":[112,130,137,147],"testing":[114],"come":[118],"from":[119],"similar":[120],"distributions,":[121],"goal":[123],"develop":[126],"labeling":[128],"function":[129],"generalizes":[131],"unobserved":[133],"connectivity":[134],"structures.":[135],"To":[136],"end,":[138],"we":[139],"employ":[140],"tangent":[144],"kernel":[145],"(GNTK)":[146],"corresponds":[148],"infinitely":[150],"wide":[151],"GNNs":[152],"find":[154],"correspondences":[155],"different":[159],"based":[161],"both":[163],"topology":[165],"features.":[169],"We":[170],"augment":[171],"capabilities":[173],"GNTK":[176],"with":[177],"residual":[178],"empirically":[181],"illustrate":[182],"its":[183],"gains":[185],"standard":[187],"benchmarks.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}