{"id":"https://openalex.org/W4226502288","doi":"https://doi.org/10.1109/tsp.2022.3160535","title":"Infinite Switching Dynamic Probabilistic Network With Bayesian Nonparametric Learning","display_name":"Infinite Switching Dynamic Probabilistic Network With Bayesian Nonparametric Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226502288","doi":"https://doi.org/10.1109/tsp.2022.3160535"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3160535","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3160535","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/A5100651077","display_name":"Wenchao Chen","orcid":"https://orcid.org/0000-0002-8875-1161"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenchao Chen","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427253","display_name":"Bo Chen","orcid":"https://orcid.org/0000-0001-5151-9388"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Chen","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101706512","display_name":"Yicheng Liu","orcid":"https://orcid.org/0000-0003-0318-7870"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicheng Liu","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100774764","display_name":"Chaojie Wang","orcid":"https://orcid.org/0000-0002-7644-7621"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaojie Wang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111118830","display_name":"Xiaojun Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I68581759","display_name":"China Academy of Launch Vehicle Technology","ror":"https://ror.org/012z62f48","country_code":"CN","type":"facility","lineage":["https://openalex.org/I68581759"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Peng","raw_affiliation_strings":["Research Academy of Rocket, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Academy of Rocket, Beijing, China","institution_ids":["https://openalex.org/I68581759"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411968","display_name":"Hongwei Liu","orcid":"https://orcid.org/0000-0003-4046-163X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Liu","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010394308","display_name":"Mingyuan Zhou","orcid":"https://orcid.org/0000-0002-4253-2780"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingyuan Zhou","raw_affiliation_strings":["McCombs School of Business, The University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"McCombs School of Business, The University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100651077"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.5956,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62750167,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"70","issue":null,"first_page":"2224","last_page":"2238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9965999722480774,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9945999979972839,"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":0.5750520825386047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5452876091003418},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5172975063323975},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5095510482788086},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5088694095611572},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.4429762661457062},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.429592490196228},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41061273217201233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5750520825386047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5452876091003418},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5172975063323975},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5095510482788086},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5088694095611572},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.4429762661457062},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.429592490196228},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41061273217201233}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3160535","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3160535","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":[{"display_name":"Reduced inequalities","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2307750574","display_name":null,"funder_award_id":"61525105","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5631434781","display_name":null,"funder_award_id":"B18039","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"},{"id":"https://openalex.org/G5861409940","display_name":null,"funder_award_id":"IIS-1812699","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7843506534","display_name":null,"funder_award_id":"U21B2006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8319798711","display_name":null,"funder_award_id":"61771361","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":95,"referenced_works":["https://openalex.org/W250167204","https://openalex.org/W592244745","https://openalex.org/W1408639475","https://openalex.org/W1517233429","https://openalex.org/W1524172054","https://openalex.org/W1551893515","https://openalex.org/W1689711448","https://openalex.org/W1783910027","https://openalex.org/W1800356822","https://openalex.org/W1973137995","https://openalex.org/W2016735230","https://openalex.org/W2027250169","https://openalex.org/W2069429561","https://openalex.org/W2085534751","https://openalex.org/W2099514122","https://openalex.org/W2105594594","https://openalex.org/W2109957730","https://openalex.org/W2110529144","https://openalex.org/W2112121851","https://openalex.org/W2112796928","https://openalex.org/W2118760499","https://openalex.org/W2119945372","https://openalex.org/W2122467621","https://openalex.org/W2127498532","https://openalex.org/W2136922672","https://openalex.org/W2147973859","https://openalex.org/W2151967501","https://openalex.org/W2157331557","https://openalex.org/W2157589572","https://openalex.org/W2158313596","https://openalex.org/W2161133254","https://openalex.org/W2167433878","https://openalex.org/W2175402905","https://openalex.org/W2185758820","https://openalex.org/W2212202474","https://openalex.org/W2216511711","https://openalex.org/W2282641050","https://openalex.org/W2529448042","https://openalex.org/W2545581354","https://openalex.org/W2547875792","https://openalex.org/W2556738441","https://openalex.org/W2567691283","https://openalex.org/W2568283273","https://openalex.org/W2624543814","https://openalex.org/W2751471435","https://openalex.org/W2753176491","https://openalex.org/W2787803546","https://openalex.org/W2895550165","https://openalex.org/W2920313172","https://openalex.org/W2925005717","https://openalex.org/W2941507491","https://openalex.org/W2951589572","https://openalex.org/W2951605425","https://openalex.org/W2962915345","https://openalex.org/W2963456629","https://openalex.org/W2964182247","https://openalex.org/W2964199361","https://openalex.org/W2964232608","https://openalex.org/W2970156808","https://openalex.org/W2982658424","https://openalex.org/W3005143445","https://openalex.org/W3035007735","https://openalex.org/W3090384423","https://openalex.org/W3155627276","https://openalex.org/W4298222718","https://openalex.org/W4391602018","https://openalex.org/W6609458005","https://openalex.org/W6617744952","https://openalex.org/W6628131027","https://openalex.org/W6631043144","https://openalex.org/W6631656437","https://openalex.org/W6638114406","https://openalex.org/W6676593269","https://openalex.org/W6676959145","https://openalex.org/W6677571061","https://openalex.org/W6683566454","https://openalex.org/W6684809622","https://openalex.org/W6685537299","https://openalex.org/W6686368241","https://openalex.org/W6688465353","https://openalex.org/W6695477072","https://openalex.org/W6697388011","https://openalex.org/W6727968406","https://openalex.org/W6728354068","https://openalex.org/W6729282377","https://openalex.org/W6729305679","https://openalex.org/W6729448088","https://openalex.org/W6730175032","https://openalex.org/W6739190660","https://openalex.org/W6743554579","https://openalex.org/W6743972897","https://openalex.org/W6744063608","https://openalex.org/W6747981893","https://openalex.org/W6754258138","https://openalex.org/W6763243348"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2146591867"],"abstract_inverted_index":{"To":[0,68],"model":[1,39,55,187],"sequentially":[2],"observed":[3],"multivariate":[4],"nonstationary":[5],"count":[6],"data,":[7],"we":[8,82,104,143],"propose":[9,145],"a":[10,16,106,115,172],"switching":[11,21,94,108],"Poisson-gamma":[12,95],"dynamical":[13,96,203],"systems":[14,97],"(SPGDS),":[15],"dynamic":[17],"probabilistic":[18,174],"network":[19],"with":[20,114],"mechanism.":[22],"Different":[23],"from":[24],"previous":[25],"models,":[26],"SPGDS":[27,53,89],"assigns":[28],"its":[29],"latent":[30,66],"variables":[31],"into":[32,88],"mixture":[33,80,87],"of":[34,71,79,156,160,167],"gamma":[35],"distributed":[36],"parameters":[37],"to":[38,65,127,137],"complex":[40,197],"sequences":[41,130],"and":[42,58,90,101,120,131,164,180,193],"describe":[43],"the":[44,76,139,153,168,185],"nonlinear":[45],"dynamics,":[46],"meanwhile,":[47],"capture":[48],"various":[49],"temporal":[50],"dependencies.":[51],"Moreover,":[52],"can":[54],"all":[56],"discrete":[57],"nonnegative":[59],"real":[60],"data":[61],"by":[62],"linking":[63],"them":[64],"counts.":[67],"take":[69],"advantage":[70],"Bayesian":[72],"nonparametrics":[73],"in":[74,133],"handling":[75],"unknown":[77],"number":[78],"components,":[81],"integrate":[83],"Dirichlet":[84],"process":[85],"(DP)":[86],"develop":[91,105],"an":[92,146],"infinite":[93,107],"(iSPGDS).":[98],"For":[99],"efficient":[100],"nonparametric":[102],"inference,":[103],"recurrent":[109],"variational":[110,121],"inference":[111,122],"network,":[112],"combined":[113],"scalable":[116,126],"hybrid":[117],"stochastic":[118],"gradient-MCMC":[119],"method,":[123],"which":[124,151],"is":[125],"large":[128],"scale":[129],"fast":[132],"out-of-sample":[134],"prediction.":[135],"Besides,":[136],"handle":[138],"time-series":[140],"categorization":[141],"task,":[142],"further":[144],"supervised":[147,181],"attention":[148,169],"iSPGDS":[149],"(attn-iSPGDS),":[150],"combines":[152],"representation":[154],"power":[155,159,166],"iSPGDS,":[157],"discriminative":[158],"deep":[161],"neural":[162],"networks,":[163],"selection":[165],"mechanism":[170],"under":[171],"principled":[173],"framework.":[175],"Experiments":[176],"on":[177,196],"both":[178],"unsupervised":[179],"tasks":[182],"demonstrate":[183],"that":[184],"proposed":[186],"not":[188],"only":[189],"has":[190],"excellent":[191],"fitting":[192],"prediction":[194],"performance":[195],"sequences,":[198],"but":[199],"also":[200],"separates":[201],"different":[202],"patterns":[204],"within":[205],"them.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
