{"id":"https://openalex.org/W4392752455","doi":"https://doi.org/10.1186/s13634-024-01128-0","title":"Time-varying graph learning from smooth and stationary graph signals with hidden nodes","display_name":"Time-varying graph learning from smooth and stationary graph signals with hidden nodes","publication_year":2024,"publication_date":"2024-03-13","ids":{"openalex":"https://openalex.org/W4392752455","doi":"https://doi.org/10.1186/s13634-024-01128-0"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-024-01128-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01128-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01128-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01128-0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020529310","display_name":"Rong Ye","orcid":"https://orcid.org/0009-0008-8704-4925"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Ye","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, 201620, China"],"raw_orcid":"https://orcid.org/0009-0008-8704-4925","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061105504","display_name":"Xueqin Jiang","orcid":"https://orcid.org/0000-0002-0414-4349"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xue-Qin Jiang","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050087930","display_name":"Hui Feng","orcid":"https://orcid.org/0000-0002-7095-0621"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Feng","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, 200433, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, 200433, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370452","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-4656-7446"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, 200433, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, 200433, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024190351","display_name":"Runhe Qiu","orcid":"https://orcid.org/0000-0002-6528-8514"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runhe Qiu","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086796043","display_name":"Xinxin Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinxin Hou","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, 201620, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5061105504"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":{"value":1790,"currency":"USD","value_usd":1790},"apc_paid":{"value":1790,"currency":"USD","value_usd":1790},"fwci":0.6971,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7406484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"2024","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9940999746322632,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9765999913215637,"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":0.6305389404296875},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.535843551158905},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.4983954429626465},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4579206705093384},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45233699679374695},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.438588410615921}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6305389404296875},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.535843551158905},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.4983954429626465},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4579206705093384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45233699679374695},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.438588410615921}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-024-01128-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01128-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01128-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:dff0491741fc42d5a001c4f810b7511c","is_oa":true,"landing_page_url":"https://doaj.org/article/dff0491741fc42d5a001c4f810b7511c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-20 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-024-01128-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01128-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01128-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1684243255","display_name":null,"funder_award_id":"2021ZD0300703","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8829195788","display_name":"\u7a00\u758f\u76f8\u4f4d\u6062\u590d\u7684\u5feb\u901f\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61971146","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392752455.pdf","grobid_xml":"https://content.openalex.org/works/W4392752455.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W305292912","https://openalex.org/W356566955","https://openalex.org/W1990488619","https://openalex.org/W1991252559","https://openalex.org/W2085712123","https://openalex.org/W2095588912","https://openalex.org/W2097596242","https://openalex.org/W2101491865","https://openalex.org/W2132555912","https://openalex.org/W2138144286","https://openalex.org/W2235146554","https://openalex.org/W2299462150","https://openalex.org/W2399508263","https://openalex.org/W2486096428","https://openalex.org/W2563279629","https://openalex.org/W2585019672","https://openalex.org/W2593294478","https://openalex.org/W2612195446","https://openalex.org/W2615556757","https://openalex.org/W2889471143","https://openalex.org/W2953689307","https://openalex.org/W2962759781","https://openalex.org/W2962886701","https://openalex.org/W2963384510","https://openalex.org/W2964012239","https://openalex.org/W2964171990","https://openalex.org/W2994097903","https://openalex.org/W3008443627","https://openalex.org/W3012969880","https://openalex.org/W3095462313","https://openalex.org/W3100282875","https://openalex.org/W3108522782","https://openalex.org/W3157999218","https://openalex.org/W3202127133","https://openalex.org/W3212653422"],"related_works":["https://openalex.org/W2903067171","https://openalex.org/W2380035736","https://openalex.org/W1927597435","https://openalex.org/W3207232533","https://openalex.org/W1568744482","https://openalex.org/W4299307887","https://openalex.org/W2952803432","https://openalex.org/W2106452164","https://openalex.org/W2389138578","https://openalex.org/W2954009223"],"abstract_inverted_index":{"Abstract":[0],"Learning":[1],"graph":[2,8,15,65,94,126,149],"structure":[3],"from":[4,48],"observed":[5,57],"signals":[6,95],"over":[7],"is":[9,164],"a":[10,42,76,105,123,146],"crucial":[11],"task":[12],"in":[13,63,136],"many":[14],"signal":[16],"processing":[17],"(GSP)":[18],"applications.":[19],"Existing":[20],"approaches":[21,36],"focus":[22],"on":[23,100,166],"inferring":[24],"static":[25],"graph,":[26],"typically":[27],"assuming":[28],"that":[29,78,92,144],"all":[30],"nodes":[31,45,54,84,135],"are":[32,46,55,96,110],"available.":[33],"However,":[34],"these":[35,119],"ignore":[37],"the":[38,52,80,93,101,131,140,176],"situation":[39],"where":[40],"only":[41,104],"subset":[43],"of":[44,82,108,133,138,148,178],"available":[47],"spatiotemporal":[49],"measurements,":[50],"and":[51,98,103,169],"remaining":[53],"never":[56],"due":[58],"to":[59,85,112,183],"application-specific":[60],"constraints,":[61],"resulting":[62],"time-varying":[64,87,125],"estimation":[66],"accuracy":[67],"declines":[68],"dramatically.":[69],"To":[70],"handle":[71],"this":[72],"problem,":[73,128],"we":[74,90,121,152],"propose":[75],"framework":[77],"consider":[79],"presence":[81],"hidden":[83,134],"identify":[86],"graph.":[88],"Specifically,":[89],"assume":[91],"smooth":[97],"stationary":[99],"graphs":[102],"small":[106],"number":[107],"edges":[109],"allowed":[111],"change":[113],"between":[114,158],"two":[115],"consecutive":[116],"graphs.":[117,160],"With":[118],"assumptions,":[120],"present":[122],"challenging":[124],"inference":[127],"which":[129],"models":[130],"influence":[132],"terms":[137],"estimating":[139],"graph-shift":[141],"operator":[142],"matrices":[143],"have":[145],"form":[147],"Laplacian.":[150],"Moreover,":[151],"emphasize":[153],"similar":[154],"edge":[155],"pattern":[156],"(column-sparsity)":[157],"different":[159],"Finally,":[161],"our":[162,179],"method":[163,180],"evaluated":[165],"both":[167],"synthetic":[168],"real-world":[170],"data.":[171],"The":[172],"experimental":[173],"results":[174],"demonstrate":[175],"advantage":[177],"when":[181],"compared":[182],"existing":[184],"benchmarking":[185],"methods.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
