{"id":"https://openalex.org/W2983911334","doi":"https://doi.org/10.23919/eusipco.2019.8902836","title":"Subsampling of Multivariate Time-Vertex Graph Signals","display_name":"Subsampling of Multivariate Time-Vertex Graph Signals","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2983911334","doi":"https://doi.org/10.23919/eusipco.2019.8902836","mag":"2983911334"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8902836","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","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/A5103241935","display_name":"Pierre Humbert","orcid":null},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210134846","display_name":"Institut d'\u00e9cologie et des sciences de l'environnement de Paris","ror":"https://ror.org/02s56xp85","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1327553481","https://openalex.org/I154202486","https://openalex.org/I197681013","https://openalex.org/I204730241","https://openalex.org/I2799535048","https://openalex.org/I2802818602","https://openalex.org/I39804081","https://openalex.org/I4210088668","https://openalex.org/I4210088668","https://openalex.org/I4210090127","https://openalex.org/I4210107625","https://openalex.org/I4210113730","https://openalex.org/I4210131494","https://openalex.org/I4210134846","https://openalex.org/I4210166444","https://openalex.org/I4405257220"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pierre Humbert","raw_affiliation_strings":["Student Member, IEEE, CMLA (CNRS, ENS Paris Saclay), Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Student Member, IEEE, CMLA (CNRS, ENS Paris Saclay), Paris, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I277688954","https://openalex.org/I4210134846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090929380","display_name":"Laurent Oudre","orcid":"https://orcid.org/0000-0002-4750-2265"},"institutions":[{"id":"https://openalex.org/I4210091279","display_name":"Universit\u00e9 Sorbonne Paris Nord","ror":"https://ror.org/0199hds37","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210091279"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Laurent Oudre","raw_affiliation_strings":["L2TI (Universit\u00e9 Paris 13), Villetaneuse, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L2TI (Universit\u00e9 Paris 13), Villetaneuse, France","institution_ids":["https://openalex.org/I4210091279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008719006","display_name":"Nicolas Vayatis","orcid":"https://orcid.org/0000-0003-4308-4681"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Vayatis","raw_affiliation_strings":["CMLA (CNRS, ENS Paris Saclay), Cachan, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CMLA (CNRS, ENS Paris Saclay), Cachan, France","institution_ids":["https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1093,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.42172481,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9943000078201294,"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":0.9943000078201294,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9932000041007996,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9890999794006348,"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":0.5923631191253662},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.5615816116333008},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.5358461141586304},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5198179483413696},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.49906349182128906},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4611648917198181},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4585305452346802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4298918843269348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38815999031066895},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3622695803642273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15522035956382751},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.12336519360542297},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.08729127049446106}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5923631191253662},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.5615816116333008},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.5358461141586304},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5198179483413696},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.49906349182128906},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4611648917198181},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4585305452346802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4298918843269348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38815999031066895},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3622695803642273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15522035956382751},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.12336519360542297},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.08729127049446106},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2019.8902836","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","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":29,"referenced_works":["https://openalex.org/W624179064","https://openalex.org/W1537592944","https://openalex.org/W1540550726","https://openalex.org/W1690143098","https://openalex.org/W1849282082","https://openalex.org/W1987484735","https://openalex.org/W1990488619","https://openalex.org/W1991252559","https://openalex.org/W1992179289","https://openalex.org/W2002996884","https://openalex.org/W2022798427","https://openalex.org/W2024165284","https://openalex.org/W2030319053","https://openalex.org/W2100729440","https://openalex.org/W2101491865","https://openalex.org/W2119699244","https://openalex.org/W2128448454","https://openalex.org/W2185199324","https://openalex.org/W2469230926","https://openalex.org/W2610174843","https://openalex.org/W2781888589","https://openalex.org/W2959406683","https://openalex.org/W2963871148","https://openalex.org/W2969273637","https://openalex.org/W3125735862","https://openalex.org/W4299350053","https://openalex.org/W6689213722","https://openalex.org/W6729291693","https://openalex.org/W6789470234"],"related_works":["https://openalex.org/W4234886518","https://openalex.org/W2389591058","https://openalex.org/W2382112581","https://openalex.org/W3124036233","https://openalex.org/W4229787472","https://openalex.org/W2486541857","https://openalex.org/W2108840191","https://openalex.org/W2759366996","https://openalex.org/W2110679372","https://openalex.org/W2354081742"],"abstract_inverted_index":{"This":[0],"article":[1],"presents":[2],"a":[3],"new":[4,38],"approach":[5],"for":[6,72],"processing":[7],"and":[8,32,75],"subsampling":[9],"multivariate":[10],"time-vertex":[11],"graph":[12,55],"signals.":[13],"The":[14],"main":[15],"idea":[16],"is":[17,44],"to":[18,33,48,59],"model":[19],"the":[20,50,54],"relationships":[21],"within":[22],"each":[23],"dimension":[24],"(time,":[25],"space,":[26],"feature":[27],"space)":[28],"with":[29],"different":[30],"graphs":[31],"merge":[34],"these":[35],"structures.":[36],"A":[37],"technique":[39],"based":[40],"on":[41,68],"tensor":[42],"formalism":[43],"provided,":[45],"which":[46],"aims":[47],"identify":[49],"frequency":[51],"support":[52],"of":[53],"signal":[56],"in":[57],"order":[58],"preserve":[60],"its":[61],"content":[62],"after":[63],"subsampling.":[64],"Results":[65],"are":[66],"provided":[67],"real":[69],"EEG":[70],"data":[71,73],"interpolation":[74],"reconstruction.":[76]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}