{"id":"https://openalex.org/W2064855647","doi":"https://doi.org/10.1109/tsp.2013.2259825","title":"Tight Wavelet Frames on Multislice Graphs","display_name":"Tight Wavelet Frames on Multislice Graphs","publication_year":2013,"publication_date":"2013-04-24","ids":{"openalex":"https://openalex.org/W2064855647","doi":"https://doi.org/10.1109/tsp.2013.2259825","mag":"2064855647"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2013.2259825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2013.2259825","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://archive-ouverte.unige.ch/unige:39809","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021046921","display_name":"Nora Leonardi","orcid":null},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]},{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","FR"],"is_corresponding":false,"raw_author_name":"Nora Leonardi","raw_affiliation_strings":["Medical Image Processing Lab (MIPLAB),&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Institute of Bioengineering","Dept. of Radiol. & Med. Inf., Univ. of Geneva, Geneva, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical Image Processing Lab (MIPLAB),&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Institute of Bioengineering","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I142476485"]},{"raw_affiliation_string":"Dept. of Radiol. & Med. Inf., Univ. of Geneva, Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003693672","display_name":"Dimitri Van De Ville","orcid":"https://orcid.org/0000-0002-2879-3861"},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]},{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","FR"],"is_corresponding":false,"raw_author_name":"Dimitri Van De Ville","raw_affiliation_strings":["Medical Image Processing Lab (MIPLAB),&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Institute of Bioengineering","Dept. of Radiol. & Med. Inf., Univ. of Geneva, Geneva, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical Image Processing Lab (MIPLAB),&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Institute of Bioengineering","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I142476485"]},{"raw_affiliation_string":"Dept. of Radiol. & Med. Inf., Univ. of Geneva, Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9743,"has_fulltext":false,"cited_by_count":127,"citation_normalized_percentile":{"value":0.93468468,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"61","issue":"13","first_page":"3357","last_page":"3367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9940000176429749,"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/wavelet","display_name":"Wavelet","score":0.6683986783027649},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5161886811256409},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.46477892994880676},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.43650171160697937},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.43406063318252563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3562557101249695},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3359556794166565},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3340068757534027},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.32705745100975037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26450806856155396},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.26079171895980835}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6683986783027649},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5161886811256409},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.46477892994880676},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.43650171160697937},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.43406063318252563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3562557101249695},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3359556794166565},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3340068757534027},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.32705745100975037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26450806856155396},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.26079171895980835}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsp.2013.2259825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2013.2259825","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:unige.ch:aou:unige:39809","is_oa":true,"landing_page_url":"https://archive-ouverte.unige.ch/unige:39809","pdf_url":null,"source":{"id":"https://openalex.org/S4306402259","display_name":"Archive ouverte UNIGE (University of Geneva)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114457229","host_organization_name":"University of Geneva","host_organization_lineage":["https://openalex.org/I114457229"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on signal processing, vol. 61, no. 13 (2013) p. 3357-3367","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.645.3653","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.645.3653","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://miplab.unige.ch/pub/leonardi1302.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:unige.ch:aou:unige:39809","is_oa":true,"landing_page_url":"https://archive-ouverte.unige.ch/unige:39809","pdf_url":null,"source":{"id":"https://openalex.org/S4306402259","display_name":"Archive ouverte UNIGE (University of Geneva)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114457229","host_organization_name":"University of Geneva","host_organization_lineage":["https://openalex.org/I114457229"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on signal processing, vol. 61, no. 13 (2013) p. 3357-3367","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W78443961","https://openalex.org/W1578099820","https://openalex.org/W1580960713","https://openalex.org/W1747101780","https://openalex.org/W1963826206","https://openalex.org/W1965820110","https://openalex.org/W1968164782","https://openalex.org/W1978632288","https://openalex.org/W1982573319","https://openalex.org/W1985281152","https://openalex.org/W1991252559","https://openalex.org/W2000215628","https://openalex.org/W2004559848","https://openalex.org/W2013912476","https://openalex.org/W2018282388","https://openalex.org/W2018342351","https://openalex.org/W2024165284","https://openalex.org/W2024489992","https://openalex.org/W2037035617","https://openalex.org/W2051398769","https://openalex.org/W2058046532","https://openalex.org/W2066047996","https://openalex.org/W2067204686","https://openalex.org/W2072701859","https://openalex.org/W2074617510","https://openalex.org/W2080161383","https://openalex.org/W2086021750","https://openalex.org/W2111512229","https://openalex.org/W2113055885","https://openalex.org/W2116111553","https://openalex.org/W2118693417","https://openalex.org/W2119741678","https://openalex.org/W2121739212","https://openalex.org/W2127006916","https://openalex.org/W2142029338","https://openalex.org/W2147469781","https://openalex.org/W2149548037","https://openalex.org/W2158787690","https://openalex.org/W2168500104","https://openalex.org/W2182304189","https://openalex.org/W4210770595","https://openalex.org/W4232078338"],"related_works":["https://openalex.org/W2104262697","https://openalex.org/W2386767533","https://openalex.org/W1811594851","https://openalex.org/W2001281573","https://openalex.org/W4285065952","https://openalex.org/W2123686096","https://openalex.org/W2353839841","https://openalex.org/W2160804081","https://openalex.org/W2111833491","https://openalex.org/W2928010092"],"abstract_inverted_index":{"We":[0,91,117,170,188,215],"present":[1],"a":[2,97,120,135,151,172,201],"framework":[3,43],"for":[4,122],"the":[5,34,45,81,93,104,109,129,143,154,183,186,190],"design":[6,121],"of":[7,26,36,85,174,192,200],"wavelet":[8,50,105],"transforms":[9],"tailored":[10],"to":[11,38,95,149,164,219],"data":[12],"defined":[13],"on":[14,61,128],"multislice":[15,123],"graphs":[16,124],"(i.e.,":[17],"multiplex":[18],"or":[19],"dynamic":[20],"graphs).":[21],"Graphs":[22,62],"with":[23],"multiple":[24,144],"types":[25],"interactions":[27],"are":[28,147],"ubiquitous":[29],"in":[30,80,103],"real":[31],"life,":[32],"motivating":[33],"extension":[35],"wavelets":[37],"these":[39,178],"complex":[40],"domains.":[41],"Our":[42],"generalizes":[44],"recently":[46],"proposed":[47],"spectral":[48,82,114],"graph":[49,115,179,223],"transform":[51],"(SGWT)":[52],"[D.":[53],"Hammond,":[54],"P.":[55],"Vandergheynst,":[56],"and":[57,107,113,153,176,204,225],"R.":[58],"Gribonval,":[59],"\u201cWavelets":[60],"via":[63],"Spectral":[64],"Graph":[65],"Theory,\u201d":[66],"Appl.":[67],"Comput.":[68],"Harmon.":[69],"Anal.,":[70],"vol.":[71],"30,":[72],"pp.":[73],"129-150,":[74],"Mar.":[75],"2011],":[76],"which":[77,100,181],"is":[78,126],"designed":[79],"(frequency)":[83],"domain":[84],"an":[86],"arbitrary":[87],"finite":[88],"weighted":[89],"graph.":[90],"extend":[92],"SGWT":[94],"form":[96,150],"tight":[98],"frame,":[99],"conserves":[101],"energy":[102],"domain,":[106],"define":[108],"relationship":[110],"between":[111],"conventional":[112],"wavelets.":[116],"then":[118],"propose":[119],"that":[125,165],"based":[127],"higher-order":[130],"singular":[131],"value":[132],"decomposition":[133,156],"(HOSVD),":[134],"powerful":[136],"tool":[137],"from":[138,177,210],"multilinear":[139],"algebra.":[140],"In":[141],"particular,":[142],"adjacency":[145],"matrices":[146],"stacked":[148],"tensor":[152],"HOSVD":[155],"provides":[157],"information":[158],"about":[159],"its":[160,217],"third-order":[161],"structure,":[162],"analogous":[163],"provided":[166],"by":[167,196,206],"matrix":[168],"factorizations.":[169],"obtain":[171],"set":[173],"\u201ceigennetworks\u201d":[175],"wavelets,":[180],"exploit":[182],"variability":[184,221],"across":[185,222],"graphs.":[187],"demonstrate":[189],"feasibility":[191],"our":[193],"method":[194],"1)":[195],"capturing":[197],"different":[198],"orientations":[199],"gray-scale":[202],"image":[203],"2)":[205],"decomposing":[207],"brain":[208],"signals":[209],"functional":[211],"magnetic":[212],"resonance":[213],"imaging.":[214],"show":[216],"effectiveness":[218],"identify":[220],"edges":[224],"provide":[226],"meaningful":[227],"decompositions.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":17},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
