{"id":"https://openalex.org/W2730106296","doi":"https://doi.org/10.24963/ijcai.2017/273","title":"Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering","display_name":"Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2730106296","doi":"https://doi.org/10.24963/ijcai.2017/273","mag":"2730106296"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/273","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/273","pdf_url":"https://www.ijcai.org/proceedings/2017/0273.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0273.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035901640","display_name":"Zhuxi Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuxi Jiang","raw_affiliation_strings":["Beijing Institute of Technology","Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063581021","display_name":"Yin Zheng","orcid":"https://orcid.org/0000-0001-7838-4794"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Zheng","raw_affiliation_strings":["Tencent AI Lab","Tencent AI Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751506","display_name":"Huachun Tan","orcid":"https://orcid.org/0000-0001-5968-103X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huachun Tan","raw_affiliation_strings":["Beijing Institute of Technology","Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049161422","display_name":"Bangsheng Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bangsheng Tang","raw_affiliation_strings":["Hulu LLC","Hulu LLC., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hulu LLC","institution_ids":[]},{"raw_affiliation_string":"Hulu LLC., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100559086","display_name":"Hanning Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanning Zhou","raw_affiliation_strings":["Hulu LLC","Hulu LLC., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hulu LLC","institution_ids":[]},{"raw_affiliation_string":"Hulu LLC., Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":651,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1965","last_page":"1972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.998199999332428,"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/T11309","display_name":"Music and Audio Processing","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7131161689758301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6940115094184875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6091570854187012},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6054917573928833},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5651503801345825},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49004876613616943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4679122567176819},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.45299622416496277},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.4469425678253174},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43182867765426636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3864316940307617},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3812006711959839}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7131161689758301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6940115094184875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6091570854187012},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6054917573928833},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5651503801345825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49004876613616943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4679122567176819},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.45299622416496277},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.4469425678253174},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43182867765426636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3864316940307617},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3812006711959839}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2017/273","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/273","pdf_url":"https://www.ijcai.org/proceedings/2017/0273.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/273","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/273","pdf_url":"https://www.ijcai.org/proceedings/2017/0273.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1938823714","display_name":null,"funder_award_id":"61620106002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4880811201","display_name":"\u57fa\u4e8e\u5f20\u91cf\u6a21\u578b\u7684\u4ea4\u901a\u6570\u636e\u91cd\u5efa\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61271376","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7804276951","display_name":null,"funder_award_id":"61271376","funder_id":"https://openalex.org/F4320323110","funder_display_name":"Beijing Institute of Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323110","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2730106296.pdf","grobid_xml":"https://content.openalex.org/works/W2730106296.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1594453127","https://openalex.org/W1950831375","https://openalex.org/W1959608418","https://openalex.org/W1975998725","https://openalex.org/W2025147484","https://openalex.org/W2057907879","https://openalex.org/W2097117768","https://openalex.org/W2108501770","https://openalex.org/W2112796928","https://openalex.org/W2118858186","https://openalex.org/W2129793592","https://openalex.org/W2132771435","https://openalex.org/W2132914434","https://openalex.org/W2141461755","https://openalex.org/W2150102617","https://openalex.org/W2163605009","https://openalex.org/W2165874743","https://openalex.org/W2173649752","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2267126114","https://openalex.org/W2280377497","https://openalex.org/W2399306074","https://openalex.org/W2409498980","https://openalex.org/W2432004435","https://openalex.org/W2434741482","https://openalex.org/W2554923929","https://openalex.org/W2556783092","https://openalex.org/W2567691283","https://openalex.org/W2618530766","https://openalex.org/W2949416428","https://openalex.org/W2950447478","https://openalex.org/W2951140085","https://openalex.org/W2953318193","https://openalex.org/W2963043971","https://openalex.org/W2963174698","https://openalex.org/W2963226019","https://openalex.org/W2963373786","https://openalex.org/W2963684088","https://openalex.org/W2964074409","https://openalex.org/W2964121744","https://openalex.org/W3038022805","https://openalex.org/W4293568373","https://openalex.org/W4295177495","https://openalex.org/W4297800839","https://openalex.org/W4298222718","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W4367312605","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W2470043383","https://openalex.org/W4380551139","https://openalex.org/W2953501176","https://openalex.org/W2965095304","https://openalex.org/W2280377497","https://openalex.org/W3034474024","https://openalex.org/W3174044702"],"abstract_inverted_index":{"Clustering":[0],"is":[1,66,82,91],"among":[2],"the":[3,29,38,55,70,73,101,110,118,139],"most":[4],"fundamental":[5],"tasks":[6],"in":[7,80,84,128],"machine":[8],"learning":[9],"and":[10,48,117,131],"artificial":[11],"intelligence.":[12],"In":[13],"this":[14,129],"paper,":[15,130],"we":[16,154],"propose":[17],"Variational":[18,32,113],"Deep":[19],"Embedding":[20],"(VaDE),":[21],"a":[22,43,49,58,63,85,88],"novel":[23],"unsupervised":[24],"generative":[25,40,152],"clustering":[26,141],"approach":[27],"within":[28],"framework":[30],"of":[31,158],"Auto-Encoder":[33],"(VAE).":[34],"Specifically,":[35],"VaDE":[36,81,136],"models":[37],"data":[39],"procedure":[41],"with":[42,123],"Gaussian":[44],"Mixture":[45],"Model":[46],"(GMM)":[47],"deep":[50],"neural":[51],"network":[52],"(DNN):":[53],"1)":[54],"GMM":[56],"picks":[57],"cluster;":[59],"2)":[60],"from":[61,146],"which":[62],"latent":[64,74,97],"embedding":[65,75],"generated;":[67],"3)":[68],"then":[69],"DNN":[71,90],"decodes":[72],"into":[76],"an":[77],"observable.":[78],"Inference":[79],"done":[83],"variational":[86],"way:":[87],"different":[89],"used":[92],"to":[93,96],"encode":[94],"observables":[95],"embeddings,":[98],"so":[99],"that":[100,135],"evidence":[102],"lower":[103],"bound":[104],"(ELBO)":[105],"can":[106],"be":[107],"optimized":[108],"using":[109,168],"Stochastic":[111],"Gradient":[112],"Bayes":[114],"(SGVB)":[115],"estimator":[116],"reparameterization":[119],"trick.":[120],"Quantitative":[121],"comparisons":[122],"strong":[124],"baselines":[125],"are":[126],"included":[127],"experimental":[132],"results":[133],"show":[134,155],"significantly":[137],"outperforms":[138],"state-of-the-art":[140],"methods":[142],"on":[143],"5":[144],"benchmarks":[145],"various":[147],"modalities.":[148],"Moreover,":[149],"by":[150],"VaDE's":[151],"nature,":[153],"its":[156],"capability":[157],"generating":[159],"highly":[160],"realistic":[161],"samples":[162],"for":[163],"any":[164],"specified":[165],"cluster,":[166],"without":[167],"supervised":[169],"information":[170],"during":[171],"training.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":27},{"year":2025,"cited_by_count":68},{"year":2024,"cited_by_count":94},{"year":2023,"cited_by_count":80},{"year":2022,"cited_by_count":84},{"year":2021,"cited_by_count":105},{"year":2020,"cited_by_count":103},{"year":2019,"cited_by_count":67},{"year":2018,"cited_by_count":23}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}