{"id":"https://openalex.org/W2636404740","doi":"https://doi.org/10.1109/icassp.2017.7952581","title":"Inferring latent states in a network influenced by neighbor activities: An undirected generative approach","display_name":"Inferring latent states in a network influenced by neighbor activities: An undirected generative approach","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2636404740","doi":"https://doi.org/10.1109/icassp.2017.7952581","mag":"2636404740"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2017.7952581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7952581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5042908114","display_name":"Buddhika L. Samarakoon","orcid":null},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Buddhika L. Samarakoon","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055723513","display_name":"Manohar N. Murthi","orcid":null},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manohar N. Murthi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018408973","display_name":"Kamal Premaratne","orcid":"https://orcid.org/0000-0001-5975-4403"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kamal Premaratne","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145608581"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0716106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"2372","last_page":"2376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9990000128746033,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9990000128746033,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9987999796867371,"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/T10799","display_name":"Data Visualization and Analytics","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7147625684738159},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6790227890014648},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.6279231309890747},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.594064474105835},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5722624659538269},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5556151270866394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5531337857246399},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.5336124897003174},{"id":"https://openalex.org/keywords/exponential-family","display_name":"Exponential family","score":0.5269418954849243},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5110622644424438},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.43375542759895325},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4042782187461853},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34665945172309875},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34660717844963074}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7147625684738159},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6790227890014648},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.6279231309890747},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.594064474105835},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5722624659538269},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5556151270866394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5531337857246399},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5336124897003174},{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.5269418954849243},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5110622644424438},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.43375542759895325},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4042782187461853},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34665945172309875},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34660717844963074},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2017.7952581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7952581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1560512119","https://openalex.org/W1934019294","https://openalex.org/W1955857676","https://openalex.org/W1968714482","https://openalex.org/W2051688597","https://openalex.org/W2097180027","https://openalex.org/W2101234009","https://openalex.org/W2120340025","https://openalex.org/W2145835757","https://openalex.org/W2147880316","https://openalex.org/W2163409259","https://openalex.org/W2168681504","https://openalex.org/W2412589610","https://openalex.org/W2905296953","https://openalex.org/W2949377321","https://openalex.org/W2964194567","https://openalex.org/W2999905431","https://openalex.org/W3122471732","https://openalex.org/W4293052541","https://openalex.org/W6633434192","https://openalex.org/W6638964526","https://openalex.org/W6640267182","https://openalex.org/W6674412744","https://openalex.org/W6675354045","https://openalex.org/W6681579763","https://openalex.org/W6682082992"],"related_works":["https://openalex.org/W2952350108","https://openalex.org/W2130561717","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W2106257677","https://openalex.org/W2964321162","https://openalex.org/W4380551139","https://openalex.org/W4375945953","https://openalex.org/W4322716735","https://openalex.org/W2952102737"],"abstract_inverted_index":{"The":[0,117],"problem":[1],"of":[2,7,32],"inferring":[3],"the":[4,92,104,110,121],"hidden":[5],"state":[6],"individual":[8],"nodes":[9],"in":[10,13,22,49,65,71,84],"social/sensor":[11],"networks":[12],"which":[14],"node":[15],"activities":[16],"affect":[17],"their":[18],"neighbors":[19,48],"is":[20,75,82],"growing":[21],"importance.":[23],"We":[24,52],"present":[25],"an":[26,55,113],"undirected":[27,123],"generative":[28],"model,":[29],"a":[30,50],"type":[31],"probabilistic":[33],"model":[34,99,111,124],"that":[35,97,120],"has":[36],"so":[37],"far":[38],"not":[39],"been":[40],"used":[41,70],"for":[42],"modeling":[43],"latent":[44,128],"variables":[45],"influenced":[46],"by":[47,86,108],"network.":[51],"also":[53],"propose":[54],"efficient":[56],"inference":[57,62],"method":[58,107],"based":[59],"on":[60],"variational":[61],"principles":[63],"which,":[64],"contrast":[66],"to":[67,77,90,131],"sampling":[68],"methods":[69,89],"most":[72],"existing":[73],"models,":[74],"scalable":[76],"larger":[78],"networks.":[79],"While":[80],"training":[81],"intractable":[83,93],"general,":[85],"using":[87,103],"stochastic":[88],"approximate":[91],"derivative,":[94],"we":[95],"show":[96],"our":[98],"can":[100,125],"be":[101],"trained":[102],"maximum":[105],"likelihood":[106],"formulating":[109],"as":[112],"exponential":[114],"family":[115],"distribution.":[116],"results":[118],"demonstrate":[119],"proposed":[122],"accurately":[126],"infer":[127],"states":[129],"compared":[130],"baseline":[132],"methods.":[133]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}