{"id":"https://openalex.org/W4312449199","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892300","title":"Symbolic Hyperdimensional Vectors with Sparse Graph Convolutional Neural Networks","display_name":"Symbolic Hyperdimensional Vectors with Sparse Graph Convolutional Neural Networks","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312449199","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892300"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892300","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5089110942","display_name":"Filip Cornell","orcid":"https://orcid.org/0000-0002-8346-610X"},"institutions":[{"id":"https://openalex.org/I4210122946","display_name":"Gavagai (Sweden)","ror":"https://ror.org/021zf9412","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210122946"]},{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Filip Cornell","raw_affiliation_strings":["School of Electrical Engineering and Computer Science KTH Royal Institute of Technology & Gavagai,Stockholm,Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science KTH Royal Institute of Technology & Gavagai,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016","https://openalex.org/I4210122946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001872735","display_name":"Jussi Karlgren","orcid":"https://orcid.org/0000-0003-4042-4919"},"institutions":[{"id":"https://openalex.org/I4210122946","display_name":"Gavagai (Sweden)","ror":"https://ror.org/021zf9412","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210122946"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Jussi Karlgren","raw_affiliation_strings":["Gavagai,Stockholm,Sweden","Gavagai, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0003-4042-4919","affiliations":[{"raw_affiliation_string":"Gavagai,Stockholm,Sweden","institution_ids":["https://openalex.org/I4210122946"]},{"raw_affiliation_string":"Gavagai, Stockholm, Sweden","institution_ids":["https://openalex.org/I4210122946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008900196","display_name":"Animesh","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Animesh","raw_affiliation_strings":["Indian Institute of Technology, Kharagpur,Centre of Excellence in Artificial Intelligence,Kharagpur,India","Centre of Excellence in Artificial Intelligence, Indian Institute of Technology, Kharagpur, Kharagpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Kharagpur,Centre of Excellence in Artificial Intelligence,Kharagpur,India","institution_ids":["https://openalex.org/I145894827"]},{"raw_affiliation_string":"Centre of Excellence in Artificial Intelligence, Indian Institute of Technology, Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041411651","display_name":"\u0160ar\u016bnas Girdzijauskas","orcid":"https://orcid.org/0000-0003-4516-7317"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sarunas Girdzijauskas","raw_affiliation_strings":["School of Electrical Engineering and Computer Science KTH Royal Institute of Technology,Stockholm,Sweden","School of Electrical Engineering and Computer Science KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science KTH Royal Institute of Technology,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016"]},{"raw_affiliation_string":"School of Electrical Engineering and Computer Science KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089110942"],"corresponding_institution_ids":["https://openalex.org/I4210122946","https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1536301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"08"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9970999956130981,"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":0.7734893560409546},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6588000059127808},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6239644289016724},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5210022926330566},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5164756774902344},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.5159902572631836},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.44136589765548706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4329957365989685},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3448777198791504},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33729350566864014}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7734893560409546},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6588000059127808},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6239644289016724},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5210022926330566},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5164756774902344},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.5159902572631836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44136589765548706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4329957365989685},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3448777198791504},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33729350566864014}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892300","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W197865394","https://openalex.org/W1573706465","https://openalex.org/W1584739173","https://openalex.org/W1596095390","https://openalex.org/W2095705004","https://openalex.org/W2112090702","https://openalex.org/W2153959628","https://openalex.org/W2155653793","https://openalex.org/W2165096765","https://openalex.org/W2405838144","https://openalex.org/W2512348510","https://openalex.org/W2580157614","https://openalex.org/W2963084622","https://openalex.org/W2963312446","https://openalex.org/W2964015378","https://openalex.org/W2965918080","https://openalex.org/W2979473749","https://openalex.org/W2980025636","https://openalex.org/W3014930333","https://openalex.org/W3035545585","https://openalex.org/W3082891099","https://openalex.org/W3091977376","https://openalex.org/W3104069545","https://openalex.org/W3122089757","https://openalex.org/W3128124761","https://openalex.org/W3139306118","https://openalex.org/W3152893301","https://openalex.org/W3158116664","https://openalex.org/W3172710683","https://openalex.org/W3177765762","https://openalex.org/W3193389962","https://openalex.org/W3198180137","https://openalex.org/W3199289026","https://openalex.org/W4205199576","https://openalex.org/W4236619680","https://openalex.org/W4241933730","https://openalex.org/W4288311604","https://openalex.org/W4294558607","https://openalex.org/W4322614756","https://openalex.org/W6635121792","https://openalex.org/W6635552158","https://openalex.org/W6674330103","https://openalex.org/W6699364125","https://openalex.org/W6713187436","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6738964360","https://openalex.org/W6764726673","https://openalex.org/W6773376115","https://openalex.org/W6790671498","https://openalex.org/W6797480598","https://openalex.org/W6821014815"],"related_works":["https://openalex.org/W3024364549","https://openalex.org/W4296209631","https://openalex.org/W4206019083","https://openalex.org/W2048865712","https://openalex.org/W1976265003","https://openalex.org/W2370378377","https://openalex.org/W4237510188","https://openalex.org/W2130160813","https://openalex.org/W2054476758","https://openalex.org/W2350613701"],"abstract_inverted_index":{"In":[0],"this":[1,92,113],"paper,":[2],"we":[3,34,47,75],"propose":[4],"a":[5,29,36,56,64],"novel":[6],"way":[7],"of":[8,21,51,66,80,87],"representing":[9],"graphs":[10],"for":[11,104,117],"processing":[12],"in":[13,55,115],"Graph":[14],"Neural":[15,58],"Networks.":[16],"We":[17,89,110],"reduce":[18,77],"the":[19,22,49,52,78,120],"dimensionality":[20],"input":[23],"data":[24,54],"by":[25,43,82],"using":[26],"Random":[27],"Indexing,":[28],"Vector":[30,44],"Symbolic":[31,45],"Architectural":[32],"framework;":[33],"implement":[35],"new":[37],"trainable":[38],"neural":[39],"layer,":[40],"also":[41],"inspired":[42],"Architectures;":[46],"leverage":[48],"sparseness":[50],"incoming":[53],"Sparse":[57],"Network":[59],"framework.":[60],"Our":[61],"experiments":[62],"on":[63],"number":[65,79],"publicly":[67],"available":[68],"datasets":[69],"and":[70,107],"standard":[71],"benchmarks":[72],"demonstrate":[73],"that":[74,112],"can":[76],"parameters":[81],"up":[83],"to":[84],"two":[85],"orders":[86],"magnitude.":[88],"show":[90],"how":[91],"parsimonious":[93],"approach":[94],"not":[95],"only":[96],"delivers":[97],"competitive":[98],"results":[99],"but":[100],"even":[101],"improves":[102],"performance":[103],"node":[105,123],"classification":[106],"link":[108],"prediction.":[109],"find":[111],"holds":[114],"particular":[116],"cases":[118],"where":[119],"graph":[121],"lacks":[122],"features.":[124]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}