{"id":"https://openalex.org/W4409796306","doi":"https://doi.org/10.1109/tpami.2025.3564188","title":"Continual Unsupervised Generative Modeling","display_name":"Continual Unsupervised Generative Modeling","publication_year":2025,"publication_date":"2025-04-25","ids":{"openalex":"https://openalex.org/W4409796306","doi":"https://doi.org/10.1109/tpami.2025.3564188","pmid":"https://pubmed.ncbi.nlm.nih.gov/40279230"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3564188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3564188","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://eprints.whiterose.ac.uk/id/eprint/227583/1/DEGM-TPAMI25.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100357221","display_name":"Fei Ye","orcid":"https://orcid.org/0000-0002-5894-2178"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Fei Ye","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","Department of Computer Science, University of York, York, UK"],"raw_orcid":"https://orcid.org/0000-0002-5894-2178","affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Department of Computer Science, University of York, York, UK","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002932489","display_name":"Adrian G. Bor\u015f","orcid":"https://orcid.org/0000-0001-7838-0021"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adrian G. Bors","raw_affiliation_strings":["Department of Computer Science, University of York, York, U.K","Department of Computer Science, University of York, York, UK"],"raw_orcid":"https://orcid.org/0000-0001-7838-0021","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of York, York, U.K","institution_ids":["https://openalex.org/I52099693"]},{"raw_affiliation_string":"Department of Computer Science, University of York, York, UK","institution_ids":["https://openalex.org/I52099693"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.089163,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"47","issue":"8","first_page":"6256","last_page":"6273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.39719998836517334,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.39719998836517334,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.669157087802887},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6492214202880859},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5211893916130066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4207439124584198},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39639511704444885}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.669157087802887},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6492214202880859},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5211893916130066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4207439124584198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39639511704444885}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2025.3564188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3564188","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40279230","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40279230","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:eprints.whiterose.ac.uk:227583","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-7838-0021>","pdf_url":"https://eprints.whiterose.ac.uk/id/eprint/227583/1/DEGM-TPAMI25.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.whiterose.ac.uk:227583","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-7838-0021>","pdf_url":"https://eprints.whiterose.ac.uk/id/eprint/227583/1/DEGM-TPAMI25.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409796306.pdf","grobid_xml":"https://content.openalex.org/works/W4409796306.grobid-xml"},"referenced_works_count":71,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W1958236864","https://openalex.org/W2001610032","https://openalex.org/W2010625607","https://openalex.org/W2064076387","https://openalex.org/W2103753221","https://openalex.org/W2112796928","https://openalex.org/W2115651492","https://openalex.org/W2160684493","https://openalex.org/W2166049352","https://openalex.org/W2194321275","https://openalex.org/W2610366607","https://openalex.org/W2617118670","https://openalex.org/W2788388592","https://openalex.org/W2963393201","https://openalex.org/W2982701845","https://openalex.org/W2997117931","https://openalex.org/W3108827478","https://openalex.org/W3109077483","https://openalex.org/W3112342379","https://openalex.org/W3136740235","https://openalex.org/W3153273997","https://openalex.org/W3168149265","https://openalex.org/W3173747377","https://openalex.org/W3175587171","https://openalex.org/W3177248386","https://openalex.org/W3187828835","https://openalex.org/W3195376085","https://openalex.org/W3197290407","https://openalex.org/W4225463540","https://openalex.org/W4225484930","https://openalex.org/W4312238419","https://openalex.org/W4312416777","https://openalex.org/W4323664467","https://openalex.org/W6610566761","https://openalex.org/W6631190155","https://openalex.org/W6636267554","https://openalex.org/W6638116569","https://openalex.org/W6638319203","https://openalex.org/W6640963894","https://openalex.org/W6684191040","https://openalex.org/W6684408796","https://openalex.org/W6719523400","https://openalex.org/W6720208624","https://openalex.org/W6732943021","https://openalex.org/W6733471323","https://openalex.org/W6738027021","https://openalex.org/W6738602802","https://openalex.org/W6741087337","https://openalex.org/W6741217325","https://openalex.org/W6743688258","https://openalex.org/W6744241929","https://openalex.org/W6745121187","https://openalex.org/W6753859023","https://openalex.org/W6754425592","https://openalex.org/W6755109808","https://openalex.org/W6757384668","https://openalex.org/W6761993158","https://openalex.org/W6762711957","https://openalex.org/W6763462227","https://openalex.org/W6764645560","https://openalex.org/W6764998394","https://openalex.org/W6767099637","https://openalex.org/W6771574350","https://openalex.org/W6771640813","https://openalex.org/W6779133958","https://openalex.org/W6779787272","https://openalex.org/W6785153168","https://openalex.org/W6797264889","https://openalex.org/W6799770525","https://openalex.org/W6849896277"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206"],"abstract_inverted_index":{"Variational":[0],"Autoencoders":[1],"(VAEs),":[2],"can":[3],"achieve":[4],"remarkable":[5],"results":[6,174],"in":[7,185],"single":[8],"tasks,":[9],"by":[10,42,60,123],"learning":[11,50,78,93,112,143],"data":[12,37],"representations,":[13],"image":[14],"generation,":[15],"or":[16],"image-to-image":[17],"translation":[18],"among":[19],"others.":[20],"However,":[21],"VAEs":[22],"suffer":[23],"from":[24],"loss":[25],"of":[26,35,57,80,92],"information":[27],"when":[28,76,102,142],"aiming":[29],"to":[30,71,161],"continuously":[31,77],"learn":[32],"a":[33,62,103,134,150],"sequence":[34],"different":[36],"domains.":[38],"This":[39,52],"is":[40,100],"caused":[41],"the":[43,55,72,89,120,125,138,163,168,177],"catastrophic":[44,58],"forgetting,":[45],"which":[46,66],"affects":[47],"all":[48],"machine":[49],"methods.":[51],"paper":[53],"addresses":[54],"problem":[56],"forgetting":[59,90],"developing":[61],"new":[63,86,109,113,144],"theoretical":[64,83],"framework":[65],"derives":[67],"an":[68],"upper":[69],"bound":[70],"negative":[73],"sample":[74],"log-likelihood":[75],"sequences":[79],"tasks.":[81,114,145],"These":[82],"derivations":[84],"provide":[85],"insights":[87],"into":[88],"behavior":[91],"models,":[94],"showing":[95],"that":[96,131,157,176],"their":[97],"optimal":[98],"performance":[99],"achieved":[101],"dynamic":[104],"mixture":[105],"expansion":[106],"model":[107,121],"adds":[108],"components":[110],"whenever":[111],"In":[115,146],"our":[116],"approach":[117],"we":[118,148],"optimize":[119],"size":[122],"introducing":[124],"Dynamic":[126,151],"Expansion":[127,152],"Graph":[128,153],"Model":[129],"(DEGM)":[130],"dynamically":[132],"builds":[133],"graph":[135,164],"structure":[136],"promoting":[137],"positive":[139,169],"knowledge":[140,170],"transfer":[141,171],"addition,":[147],"propose":[149],"Adaptive":[154],"Mechanism":[155],"(DEGAM)":[156],"generates":[158],"adaptive":[159],"weights":[160],"regulate":[162],"structure,":[165],"further":[166],"improving":[167],"effectiveness.":[172],"Experimental":[173],"show":[175],"proposed":[178],"methodology":[179],"performs":[180],"better":[181],"than":[182],"other":[183],"baselines":[184],"continual":[186],"learning.":[187]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}