{"id":"https://openalex.org/W3015304892","doi":"https://doi.org/10.1109/icassp40776.2020.9054072","title":"On The Stability of Polynomial Spectral Graph Filters","display_name":"On The Stability of Polynomial Spectral Graph Filters","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015304892","doi":"https://doi.org/10.1109/icassp40776.2020.9054072","mag":"3015304892"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5029247834","display_name":"Henry Kenlay","orcid":"https://orcid.org/0000-0002-6741-2494"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Henry Kenlay","raw_affiliation_strings":["University of Oxford"],"affiliations":[{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072466998","display_name":"Dorina Thanou","orcid":"https://orcid.org/0000-0003-2319-4832"},"institutions":[{"id":"https://openalex.org/I4210122261","display_name":"Swiss Data Science Center","ror":"https://ror.org/02hdt9m26","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I2799323385","https://openalex.org/I35440088","https://openalex.org/I4210122261","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Dorina Thanou","raw_affiliation_strings":["Swiss Data Science Center"],"affiliations":[{"raw_affiliation_string":"Swiss Data Science Center","institution_ids":["https://openalex.org/I4210122261"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101579932","display_name":"Xiaowen Dong","orcid":"https://orcid.org/0000-0002-1143-9786"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiaowen Dong","raw_affiliation_strings":["University of Oxford"],"affiliations":[{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029247834"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":1.903,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.88709432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5350","last_page":"5354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9909999966621399,"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":0.972100019454956,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.5265085101127625},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.5219992399215698},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5164928436279297},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45048168301582336},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4419594705104828},{"id":"https://openalex.org/keywords/butterfly-graph","display_name":"Butterfly graph","score":0.4181172251701355},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.41621652245521545},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4137137830257416},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36553943157196045}],"concepts":[{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.5265085101127625},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.5219992399215698},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5164928436279297},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45048168301582336},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4419594705104828},{"id":"https://openalex.org/C18819970","wikidata":"https://www.wikidata.org/wiki/Q3035340","display_name":"Butterfly graph","level":5,"score":0.4181172251701355},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.41621652245521545},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4137137830257416},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36553943157196045}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:c629d35b-7102-4daf-a0d1-987ec55673f5","is_oa":false,"landing_page_url":"https://ora.ox.ac.uk/objects/uuid:c629d35b-7102-4daf-a0d1-987ec55673f5","pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements","raw_type":"Conference item"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W149522324","https://openalex.org/W1479807131","https://openalex.org/W1483804921","https://openalex.org/W1551404194","https://openalex.org/W1578099820","https://openalex.org/W1949337326","https://openalex.org/W2008620264","https://openalex.org/W2025324442","https://openalex.org/W2101491865","https://openalex.org/W2130354913","https://openalex.org/W2610267922","https://openalex.org/W2796983212","https://openalex.org/W2803831897","https://openalex.org/W2889406344","https://openalex.org/W2943959761","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W3007134945","https://openalex.org/W3098276446","https://openalex.org/W4210257598","https://openalex.org/W6633104551","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6762304760","https://openalex.org/W6807384801"],"related_works":["https://openalex.org/W2389330739","https://openalex.org/W2954009223","https://openalex.org/W1927597435","https://openalex.org/W3207232533","https://openalex.org/W1002309053","https://openalex.org/W4299307887","https://openalex.org/W2903067171","https://openalex.org/W2952803432","https://openalex.org/W4318995835","https://openalex.org/W3100627703"],"abstract_inverted_index":{"Spectral":[0],"graph":[1,18,28,45,75,87,118,128],"filters":[2,29,46,76,129],"are":[3,47,77],"a":[4,64,97,109],"key":[5],"component":[6],"in":[7,84,108,115],"state-of-the-art":[8],"machine":[9],"learning":[10,33,65],"models":[11],"used":[12],"for":[13,32],"graph-based":[14],"learning,":[15],"such":[16],"as":[17,52],"neural":[19],"networks.":[20],"For":[21],"certain":[22],"tasks":[23],"stability":[24],"of":[25,39,96,104],"the":[26,37,82,85,101,105,113,116],"spectral":[27,44],"is":[30],"important":[31],"suitable":[34],"representations.":[35],"Understanding":[36],"type":[38],"structural":[40,98,133],"perturbation":[41],"to":[42,53,59,63,81],"which":[43],"robust":[48,127],"lets":[49],"us":[50],"reason":[51],"when":[54],"we":[55,70],"may":[56],"expect":[57],"them":[58],"be":[60],"well":[61],"suited":[62],"task.":[66],"In":[67],"this":[68],"work,":[69],"first":[71],"prove":[72],"that":[73,94],"polynomial":[74],"stable":[78],"with":[79],"respect":[80],"change":[83,114],"normalised":[86,117],"Laplacian":[88],"matrix.":[89],"We":[90],"then":[91],"show":[92],"empirically":[93],"properties":[95],"perturbation,":[99],"specifically":[100],"relative":[102],"locality":[103],"edges":[106],"removed":[107],"binary":[110],"graph,":[111],"effect":[112],"Laplacian.":[119],"Together,":[120],"our":[121],"results":[122],"have":[123],"implications":[124],"on":[125],"designing":[126],"and":[130],"representations":[131],"under":[132],"perturbation.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
