{"id":"https://openalex.org/W4392123178","doi":"https://doi.org/10.1080/10618600.2024.2319162","title":"A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices","display_name":"A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices","publication_year":2024,"publication_date":"2024-02-23","ids":{"openalex":"https://openalex.org/W4392123178","doi":"https://doi.org/10.1080/10618600.2024.2319162"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2319162","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2319162","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-04150292v3/file/jcgs-article_rev%20%281%29.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080113669","display_name":"Giulia Marchello","orcid":"https://orcid.org/0000-0002-3017-3338"},"institutions":[{"id":"https://openalex.org/I201841394","display_name":"Universit\u00e9 C\u00f4te d'Azur","ror":"https://ror.org/019tgvf94","country_code":"FR","type":"education","lineage":["https://openalex.org/I201841394"]},{"id":"https://openalex.org/I4210112930","display_name":"Laboratoire Jean-Alexandre Dieudonn\u00e9","ror":"https://ror.org/0274zdr66","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I201841394","https://openalex.org/I4210112930","https://openalex.org/I4210141950"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Giulia Marchello","raw_affiliation_strings":["Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, Laboratoire J.A.Dieudonn\u00e9, Maasai team"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, Laboratoire J.A.Dieudonn\u00e9, Maasai team","institution_ids":["https://openalex.org/I4210112930","https://openalex.org/I201841394"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033119788","display_name":"Marco Corneli","orcid":"https://orcid.org/0000-0002-9361-0080"},"institutions":[{"id":"https://openalex.org/I4210141055","display_name":"Cultures et Environnements. Pr\u00e9histoire, Antiquit\u00e9, Moyen \u00c2ge","ror":"https://ror.org/04n9van71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I201841394","https://openalex.org/I2802818602","https://openalex.org/I2802818602","https://openalex.org/I4210102700","https://openalex.org/I4210102700","https://openalex.org/I4210107625","https://openalex.org/I4210141055","https://openalex.org/I4210155116"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Marco Corneli","raw_affiliation_strings":["Universit\u00e9 C\u00f4te d\u2019Azur, Laboratoire CEPAM"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 C\u00f4te d\u2019Azur, Laboratoire CEPAM","institution_ids":["https://openalex.org/I4210141055"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051332724","display_name":"Charles Bouveyron","orcid":"https://orcid.org/0000-0002-6956-4491"},"institutions":[{"id":"https://openalex.org/I201841394","display_name":"Universit\u00e9 C\u00f4te d'Azur","ror":"https://ror.org/019tgvf94","country_code":"FR","type":"education","lineage":["https://openalex.org/I201841394"]},{"id":"https://openalex.org/I4210112930","display_name":"Laboratoire Jean-Alexandre Dieudonn\u00e9","ror":"https://ror.org/0274zdr66","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I201841394","https://openalex.org/I4210112930","https://openalex.org/I4210141950"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Charles Bouveyron","raw_affiliation_strings":["Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, Laboratoire J.A.Dieudonn\u00e9, Maasai team"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 C\u00f4te d\u2019Azur, Inria, CNRS, Laboratoire J.A.Dieudonn\u00e9, Maasai team","institution_ids":["https://openalex.org/I4210112930","https://openalex.org/I201841394"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080113669"],"corresponding_institution_ids":["https://openalex.org/I201841394","https://openalex.org/I4210112930"],"apc_list":null,"apc_paid":null,"fwci":1.5123,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.84232901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"33","issue":"4","first_page":"1224","last_page":"1239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9954000115394592,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9954000115394592,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9940000176429749,"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/T10057","display_name":"Face and Expression Recognition","score":0.9908999800682068,"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/cluster-analysis","display_name":"Cluster analysis","score":0.5566992163658142},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5120978355407715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4892270565032959},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.48358839750289917},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.474789559841156},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38546842336654663},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36022570729255676},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33077573776245117},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.32756537199020386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3185572028160095},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.18138283491134644}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5566992163658142},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5120978355407715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4892270565032959},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.48358839750289917},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.474789559841156},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38546842336654663},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36022570729255676},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33077573776245117},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32756537199020386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3185572028160095},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.18138283491134644},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10618600.2024.2319162","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2319162","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-04150292v3","is_oa":true,"landing_page_url":"https://hal.science/hal-04150292","pdf_url":"https://hal.science/hal-04150292v3/file/jcgs-article_rev%20%281%29.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Computational and Graphical Statistics, 2024, 33 (4), pp.1224-1239. &#x27E8;10.1080/10618600.2024.2319162&#x27E9;","raw_type":"Journal articles"},{"id":"pmh:oai:HAL:hal-04865734v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04865734","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Computational and Graphical Statistics, 2024, 33 (4), pp.1224-1239. &#x27E8;10.1080/10618600.2024.2319162&#x27E9;","raw_type":"Journal articles"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04150292v3","is_oa":true,"landing_page_url":"https://hal.science/hal-04150292","pdf_url":"https://hal.science/hal-04150292v3/file/jcgs-article_rev%20%281%29.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Computational and Graphical Statistics, 2024, 33 (4), pp.1224-1239. &#x27E8;10.1080/10618600.2024.2319162&#x27E9;","raw_type":"Journal articles"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2113015678","display_name":null,"funder_award_id":"ANR-19-P3IA-0002","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G8202435710","display_name":null,"funder_award_id":"19-P3IA-0002","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G8318455765","display_name":null,"funder_award_id":"ANR-19","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392123178.pdf","grobid_xml":"https://content.openalex.org/works/W4392123178.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W418587746","https://openalex.org/W1522301498","https://openalex.org/W1694128711","https://openalex.org/W1783910027","https://openalex.org/W1869098353","https://openalex.org/W1929593512","https://openalex.org/W1970884397","https://openalex.org/W1982509351","https://openalex.org/W1983865742","https://openalex.org/W1984007049","https://openalex.org/W1988283995","https://openalex.org/W2033403400","https://openalex.org/W2037299692","https://openalex.org/W2043545458","https://openalex.org/W2049633694","https://openalex.org/W2075657928","https://openalex.org/W2080295262","https://openalex.org/W2087906470","https://openalex.org/W2105480448","https://openalex.org/W2109820980","https://openalex.org/W2119634512","https://openalex.org/W2133576408","https://openalex.org/W2144799688","https://openalex.org/W2168878667","https://openalex.org/W2434205482","https://openalex.org/W2597328883","https://openalex.org/W2615276431","https://openalex.org/W2626752915","https://openalex.org/W2794266768","https://openalex.org/W2890327461","https://openalex.org/W2896706527","https://openalex.org/W2899771611","https://openalex.org/W2950867735","https://openalex.org/W2996041149","https://openalex.org/W2996961133","https://openalex.org/W3008151628","https://openalex.org/W3012326351","https://openalex.org/W3128977397","https://openalex.org/W3198135059","https://openalex.org/W3204176123","https://openalex.org/W4237840503","https://openalex.org/W4240253383","https://openalex.org/W4280491856","https://openalex.org/W4319444044","https://openalex.org/W4392488419"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W4298130764","https://openalex.org/W2014494654","https://openalex.org/W2804364458","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W2095350775","https://openalex.org/W2990323019","https://openalex.org/W2132641928"],"abstract_inverted_index":{"The":[0,122],"simultaneous":[1],"clustering":[2],"of":[3,7,58,69,83,102,118,156,163],"observations":[4,75],"and":[5,32,79,106,111,149],"features":[6],"datasets":[8,152],"(known":[9],"as":[10,15],"co-clustering)":[11],"has":[12],"recently":[13],"emerged":[14],"a":[16,49,77],"central":[17],"machine":[18],"learning":[19],"application":[20],"to":[21,140],"summarize":[22],"massive":[23],"datasets.":[24],"However,":[25],"most":[26],"existing":[27],"models":[28],"focus":[29],"on":[30,125,147],"continuous":[31],"dense":[33],"data":[34,59,107],"in":[35,99,138,160],"stationary":[36],"scenarios,":[37],"where":[38],"cluster":[39,104],"assignments":[40],"do":[41],"not":[42],"evolve":[43],"over":[44],"time.":[45],"This":[46],"work":[47],"introduces":[48],"novel":[50],"latent":[51],"block":[52,80],"model":[53,66],"for":[54],"the":[55,74,91,100,109,142,154,157,161],"dynamic":[56],"co-clustering":[57],"matrices":[60],"with":[61,90],"high":[62],"sparsity.":[63],"To":[64,95],"properly":[65],"this":[67],"type":[68],"data,":[70],"we":[71],"assume":[72],"that":[73],"follow":[76],"time":[78],"dependent":[81],"mixture":[82],"zero-inflated":[84],"distributions,":[85],"thus,":[86],"combining":[87],"stochastic":[88],"processes":[89],"time-varying":[92],"sparsity":[93,112],"modeling.":[94],"detect":[96],"abrupt":[97],"changes":[98],"dynamics":[101],"both":[103],"memberships":[105],"sparsity,":[108],"mixing":[110],"proportions":[113],"are":[114],"modeled":[115],"through":[116],"systems":[117],"ordinary":[119],"differential":[120],"equations.":[121],"inference":[123],"relies":[124],"an":[126],"original":[127],"variational":[128],"procedure":[129],"whose":[130],"maximization":[131],"step":[132],"trains":[133],"fully":[134],"connected":[135],"neural":[136],"networks":[137],"order":[139],"solve":[141],"dynamical":[143],"systems.":[144],"Numerical":[145],"experiments":[146],"simulated":[148],"real":[150],"world":[151],"demonstrate":[153],"effectiveness":[155],"proposed":[158],"methodology":[159],"context":[162],"count":[164],"data.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}
