{"id":"https://openalex.org/W2135131134","doi":"https://doi.org/10.1109/tsp.2013.2243445","title":"Attribute Fusion in a Latent Process Model for Time Series of Graphs","display_name":"Attribute Fusion in a Latent Process Model for Time Series of Graphs","publication_year":2013,"publication_date":"2013-01-28","ids":{"openalex":"https://openalex.org/W2135131134","doi":"https://doi.org/10.1109/tsp.2013.2243445","mag":"2135131134"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2013.2243445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2013.2243445","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056784746","display_name":"Minh Tang","orcid":"https://orcid.org/0000-0003-1420-7187"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minh Tang","raw_affiliation_strings":["Department of AppliedMathematics and Statistics, John Hopkins University, Baltimore, MD, USA","Department of Applied Mathematics and Statistics, Johns Hopkins University , Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of AppliedMathematics and Statistics, John Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University , Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021862004","display_name":"Youngser Park","orcid":"https://orcid.org/0000-0002-3978-5533"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Youngser Park","raw_affiliation_strings":["Center of Imaging Science, John Hopkins University, Baltimore, MD, USA","Center of Imaging Science, Johns Hopkins University, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Imaging Science, John Hopkins University, Baltimore, MD, USA","institution_ids":[]},{"raw_affiliation_string":"Center of Imaging Science, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046793514","display_name":"Nam H. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nam H. Lee","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, John Hopkins University, Baltimore, MD, USA","Department of Applied Mathematics and Statistics, Johns Hopkins University , Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, John Hopkins University, Baltimore, MD, USA","institution_ids":[]},{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University , Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031834098","display_name":"Carey E. Priebe","orcid":"https://orcid.org/0000-0002-0139-7201"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carey E. Priebe","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, John Hopkins University, Baltimore, MD, USA","Department of Applied Mathematics and Statistics, Johns Hopkins University , Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, John Hopkins University, Baltimore, MD, USA","institution_ids":[]},{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University , Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":1.4989,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.83424077,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"61","issue":"7","first_page":"1721","last_page":"1732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9954000115394592,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9954000115394592,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9933000206947327,"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/inference","display_name":"Inference","score":0.6461427807807922},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6205690503120422},{"id":"https://openalex.org/keywords/random-graph","display_name":"Random graph","score":0.5999228358268738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5942879915237427},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5622624158859253},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5064414739608765},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.5012838840484619},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39625686407089233},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3786258101463318},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.37860244512557983},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3501591980457306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32287782430648804},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3023150563240051},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1349688470363617}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6461427807807922},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6205690503120422},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.5999228358268738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5942879915237427},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5622624158859253},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5064414739608765},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.5012838840484619},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39625686407089233},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3786258101463318},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.37860244512557983},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3501591980457306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32287782430648804},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3023150563240051},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1349688470363617},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2013.2243445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2013.2243445","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.49000000953674316,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W3872587","https://openalex.org/W1848620603","https://openalex.org/W1980347317","https://openalex.org/W1987349051","https://openalex.org/W1988789570","https://openalex.org/W2004559848","https://openalex.org/W2016735295","https://openalex.org/W2018777436","https://openalex.org/W2026565928","https://openalex.org/W2040840530","https://openalex.org/W2066459332","https://openalex.org/W2076736556","https://openalex.org/W2081324234","https://openalex.org/W2093308813","https://openalex.org/W2102907934","https://openalex.org/W2102946917","https://openalex.org/W2107107106","https://openalex.org/W2111565546","https://openalex.org/W2120121938","https://openalex.org/W2140273660","https://openalex.org/W2154756352","https://openalex.org/W2158787690","https://openalex.org/W2163655603","https://openalex.org/W2180313959","https://openalex.org/W3098531157","https://openalex.org/W3105714181","https://openalex.org/W4210770595","https://openalex.org/W4302856910","https://openalex.org/W4312512934","https://openalex.org/W6676274861"],"related_works":["https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W2362286668","https://openalex.org/W2133382151","https://openalex.org/W2153339597","https://openalex.org/W1528412344"],"abstract_inverted_index":{"Hypothesis":[0],"testing":[1],"on":[2,63,166],"time":[3,56,80],"series":[4,57,81],"of":[5,46,58,82,109],"attributed":[6,83,96],"graphs":[7,59],"has":[8],"applications":[9],"in":[10,67,123],"diverse":[11],"areas,":[12],"e.g.,":[13],"social":[14],"network":[15],"analysis":[16],"(wherein":[17,26,36],"vertices":[18,27,37],"represent":[19,38],"individual":[20],"actors":[21],"or":[22,30,40],"organizations),":[23],"connectome":[24],"inference":[25],"are":[28,99],"neurons":[29],"brain":[31],"regions)":[32],"and":[33,71,101,127],"text":[34],"processing":[35],"authors":[39],"documents).":[41],"We":[42],"consider":[43],"the":[44,51,64,139,147,150],"problem":[45],"anomaly/change":[47],"point":[48],"detection":[49,105],"given":[50],"latent":[52,76],"process":[53,77],"model":[54,78,152,161],"for":[55,79,104,134],"with":[60],"categorical":[61],"attributes":[62],"edges":[65],"presented":[66],"[N.":[68],"H.":[69],"Lee":[70],"C.":[72],"E.":[73],"Priebe,":[74],"\u201cA":[75],"random":[84],"graphs,\u201d":[85],"Statist.":[86],"Inference":[87],"Stoch.":[88],"Process.,":[89],"vol.":[90],"14,":[91],"pp.":[92],"231-253,":[93],"2011].":[94],"Various":[95],"graph":[97],"invariants":[98],"considered,":[100],"their":[102],"power":[103],"as":[106],"a":[107,110],"function":[108],"linear":[111],"fusion":[112],"parameter":[113],"is":[114,119,153],"presented.":[115],"Our":[116],"main":[117],"result":[118],"that":[120,149,159],"inferential":[121],"performance":[122],"mathematically":[124],"tractable":[125],"first-order":[126],"second-order":[128],"approximation":[129,160],"models":[130],"does":[131],"provide":[132],"guidance":[133],"methodological":[135],"choices":[136],"applicable":[137],"to":[138,146],"exact":[140,151],"(realistic":[141],"but":[142],"intractable)":[143],"model.":[144],"Furthermore,":[145],"extent":[148],"realistic,":[154],"we":[155],"may":[156],"tentatively":[157],"conclude":[158],"investigations":[162],"have":[163],"some":[164],"bearing":[165],"real":[167],"data":[168],"applications.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
